Diagnostics & Genomics

AliveCor is the natural counterpart to iRhythm and the two divide cardiac artificial intelligence between them along a clean line. iRhythm records continuously for up to 14 days and answers what rhythm this patient has over time. AliveCor takes a recording lasting seconds and answers what is happening now, which is a different clinical question and a different regulatory problem. The company began in consumer grade personal electrocardiography, with the KardiaMobile family placing FDA cleared single and six lead recording in a patient's hand, and it describes itself as the leading provider of cleared personal electrocardiogram devices. The record's centre of gravity has since moved toward the clinic. Kardia 12L, launched June 2024, is the current flagship and the technical claim behind it is unusual. A single cable and five electrodes acquire eight diagnostic bandwidth leads, from which KAI 12L, the artificial intelligence powering the system, reconstructs and interprets a full 12 lead study. That reduced leadset design is why the device is pocket sized, and it is also why the intelligence is doing something a conventional machine does not have to: inferring what the missing leads would show. The cleared scope is the largest of any single artificial intelligence system in this index. KAI 12L launched with 35 cardiac determinations, 14 arrhythmias and 21 morphologies, and a further clearance in January 2026 added short PR interval, atrial bigeminy, ventricular bigeminy, left axis deviation and right axis deviation, bringing the total to 39. It is described as the first cleared artificial intelligence able to detect a heart attack from a reduced leadset, covering acute myocardial infarction and common forms of cardiac ischemia. The system is built on multiple deep neural network algorithms trained and validated on more than 1.75 million electrocardiograms from leading United States medical centres. Deployment and evidence are both concrete. Since launch the system has reached more than 250 clinical practices in the United States and expanded into India, Australia and New Zealand, with European regulatory review ongoing. The company reports use on tens of thousands of patients and identification of more than 4,000 cases of myocardial infarction and ischemia. A peer reviewed study in Heart Rhythm O2 found the system reduced electrocardiogram acquisition time by 29 percent. In 2025 the Centers for Medicare and Medicaid Services approved payment in hospital outpatient settings. Based in Mountain View, California, led by chief executive Priya Abani, and named to the inaugural TIME World's Top Health Tech Companies list in 2025. An InstantQT product for remote point of care recording launched in Europe in July 2024.

iRhythm is the largest absence this index had in remote monitoring, and it is one of the few companies anywhere whose artificial intelligence claim rests on a landmark paper in a top tier medical journal. The product is a service rather than a device sold alone. A Zio adhesive patch records continuous single lead electrocardiography for up to 14 days, the patient returns it, and the recording passes through a deep learned algorithm before qualified cardiac technicians verify the output and a physician receives a report. The company is explicit that artificial intelligence and human review operate together, describing the algorithm as verified by technicians rather than as autonomous, and the reported result is 99 percent physician agreement with the end of wear report. The scale of the training data is the moat and the company states it plainly: more than 750 million hours of curated heartbeat data, described as the largest repository of labelled electrocardiographic patient data in the world. That is the direct consequence of running a service rather than selling a device, because every patch returned is another labelled recording, and it is why average rhythm detection sensitivity is stated as having improved 21 percent since the algorithm's creation in 2010, moving from machine learned to deep learned methods. The scientific anchor is Hannun and colleagues in Nature Medicine in 2019, demonstrating a deep neural network classifying a broad range of arrhythmias at diagnostic performance comparable to cardiologists. The company describes more than 100 original research manuscripts covering the service, including comparative effectiveness work in the American Heart Journal and a Medicare beneficiary utilisation study, and it publishes citations rather than adjectives. Regulatory coverage is broad: 510(k) clearance in the United States, CE marking, UKCA marking and Japanese approval, with the deep learned algorithm available in the United States, European Union, Switzerland, United Kingdom and Japan. Thirteen arrhythmia classes are detected and the company states these were included in the procedure code validation process. A separate wrist worn product, the Zio Watch, was cleared with Verily under the ZEUS software for detecting atrial fibrillation and characterising its burden over time. Around the analysis sits a provider portal, electronic health record integration and a patient application. The company is publicly traded and led by chief executive Quentin Blackford. One thing a reader should weigh. The deep learned algorithm is not available in every market where the devices are sold, which the company discloses in a footnote, so the artificial intelligence a buyer is assessing may not be the artificial intelligence they receive.

Panakeia makes the most technically ambitious claim in this lane. Every other pathology vendor here reads morphology from an image and reports what a pathologist could in principle see. Panakeia predicts molecular status from the same image, inferring microsatellite instability and mismatch repair deficiency directly from routine haematoxylin and eosin stained slides, without sequencing, immunohistochemistry or any additional laboratory test. The company describes itself as the world's first in silico multi omics company. The clinical rationale is straightforward and the value is in the time. Microsatellite instability and mismatch repair deficiency status determines immunotherapy eligibility in colorectal cancer and identifies Lynch syndrome, a hereditary cancer predisposition with implications for the patient's relatives as well as the patient. That status normally arrives weeks after diagnosis through separate molecular testing. PANProfiler Colorectal returns it in minutes from an image the laboratory has already produced, with no change to existing workflow and no additional tissue consumed. The validation is the strongest in this lane and it was not conducted by the company. A blinded multi site clinical validation led by the University of Leeds and Leeds Teaching Hospitals NHS Trust was published in npj Digital Medicine in January 2026 and is described as the largest real world blinded multi site validation of artificial intelligence enabled molecular profiling from routine diagnostic images. Earlier blinded multi site results were presented at the ASCO gastrointestinal cancers symposium in January 2025, and proof of concept across more than 30 cancer indications was published in Communications Medicine in 2024. The company also submits to comparison it does not control. Its breast product was included in an independent multi vendor study assessing agreement on HER2 expression, alongside nine other models and three pathologists. The published result is uncomfortable for the whole field rather than for Panakeia specifically: the ten models agreed with each other 65 percent of the time, artificial intelligence and pathologists agreed 65 percent of the time, and the three pathologists agreed with each other 70 percent of the time, with low HER2 expression difficult for both. Participating in work that produces that finding is a form of transparency almost nobody in this index practises. The company also participates in the Friends of Cancer Research digital pathology agreement project and PANProfiler Colorectal has been selected for the UK regulator's AI Airlock programme for real world evaluation of artificial intelligence medical devices. Regulatory status is split deliberately. Two clinical products for colorectal and breast cancer are UKCA marked and clinically deployed in the United Kingdom, while the wider PANProfiler platform covering more than 30 cancer types is research use only, sold to pharmaceutical companies for trial screening, biomarker discovery and patient selection. Headquartered in Cambridge, United Kingdom, founded and led by chief executive Pahini Pandya.

Qritive is the closest thing in this index to Deep Bio's counterpart, and the pair are worth reading together. Both are Asian computational pathology companies anchored on prostate. Deep Bio builds algorithms only and distributes them through other companies' platforms. Qritive builds both the algorithms and the platform they run in, and then also distributes the algorithms into competitors' platforms, which is an unusual position to hold on both sides of the same market. Pantheon is the platform: a vendor agnostic, cloud ready image management system supporting all major whole slide image formats, covering case management, slide viewing, artificial intelligence supported analysis and structured reporting, with telepathology and remote consultation. Vendor agnosticism is stated as a design commitment and appears to be genuine, since the company's own modules also run inside competitors' systems. The QAi module family is the intelligence and it spans more cancers than most specialists attempt: prostate, colon, breast, lymph node and gastric, plus immunohistochemistry marker quantification and lymph node metastasis detection. QAi Prostate analyses whole slide images of core needle biopsies, identifies prostatic adenocarcinoma, segments and classifies benign and malignant areas, and reports tumour size and percentage per slide or region of interest. In its most recent deployment the prostate module is described as detecting malignant glands, identifying tumour architecture, grading according to International Society of Urological Pathology criteria, characterising Gleason patterns, quantifying tumour burden and flagging suspicious regions, with final clinical decisions remaining with pathologists. The regulatory position is real and modest in class. Pantheon is registered with Singapore's Health Sciences Authority as a class A medical device and is CE marked, described in one account as CE marked for in vitro diagnostic use, and the company holds ISO 13485 certification for design, development, manufacture, distribution and installation of software medical devices. Deployment is the strongest evidence and it is geographically unusual. Three Indian institutions adopted Pantheon and the artificial intelligence modules, including Metropolis Healthcare, the Rajiv Gandhi Cancer Institute and CORE Diagnostics. In June 2026 M42's National Reference Laboratory integrated the prostate module into its workflow at Cleveland Clinic Abu Dhabi, introducing artificial intelligence prostate diagnostics in the United Arab Emirates. The prostate grading module also runs on Roche's digital pathology platform, and the modules integrate with Corista's DP3. Founded in 2017 in Singapore by Dr Aneesh Sathe, a mechanobiology doctorate who built computer vision systems for identifying cancer cells, and Dr Kaveh Taghipour, whose doctorate is in natural language processing, both from the National University of Singapore. Operations extend to India and the United States, and the company is led by chief executive Bruno Occhipinti.

Deep Bio is a narrow specialist in a lane full of platforms, and the narrowness is the point. The company builds deep learning algorithms for prostate cancer histopathology and has taken them through a regulator rather than to a marketplace. DeepDx Prostate analyses whole slide images of haematoxylin and eosin stained prostate core needle biopsies, detecting and localising malignancy on Gleason patterns and quantifying tumour to tissue ratios, in a stated 30 seconds per core. Reported performance is 99 percent sensitivity and 97 percent specificity. Output is delivered as colour coded heatmap overlays highlighting suspect lesions alongside quantitative measures, and the company redesigned its reports specifically because pathologists in early deployments were not noticing the heatmaps, which is an unusually candid account of an adoption problem. DeepDx Prostate Pro extends this from detection to grading. It classifies histological severity automatically and generates Gleason grades and scores, returning a no grade result where tissue does not fall within the system rather than forcing a classification. In evaluation studies it showed 98.7 percent concordance in grade group classification and 96.9 percent in no grade classification against a reference standard created by three pathologists. The regulatory record is the strongest element and the firsts are real rather than promotional. DeepDx Prostate was the first artificial intelligence pathology tool in Korea to receive class 3 in vitro diagnostic device approval from the Ministry of Food and Drug Safety. DeepDx Prostate Pro then received what the company describes as the world's first regulatory clearance for an artificial intelligence device classifying prostate cancer severity by Gleason grade, again as a class 3 device, and was later designated an innovative product by Korean regulators and by the public procurement service. The products are CE marked. The evidence base is genuinely independent in part. An external validation study was published in Modern Pathology in October 2022 with named academic authors, and the company reports participating in the United States and Canadian Academy of Pathology meeting annually since 2018 with papers each year. Training data reportedly included thousands of slides at approval with more than 500,000 core images from the United States added subsequently for quality control. Distribution is through other companies' platforms rather than a sales force. The prostate algorithm is integrated into Roche Diagnostics' Navify Digital Pathology, Visiopharm's App Center, and Techcyte's platform, the latter two both separately indexed here. Five South Korean hospitals ran trial deployments ahead of full workflow integration. Based in Seoul, with work extending to breast cancer lesion differentiation and frozen section analysis.

Lumea is built on a claim the rest of this lane does not make: that digital pathology fails upstream of the software, and no viewer however sophisticated can compensate for fragmented, disoriented or compromised tissue. The company therefore starts at the biopsy rather than at the scanner, and the record covers four layers rather than one. The first is physical. BxChip is a patented sectionable matrix holding up to six biopsy cores through laboratory processing, with a stated average increase of 14.5 percent in histologic tissue surface area, and the matrix is stated not to interfere with immunohistochemistry, in situ hybridisation or sequencing. BxBoard and BxFrame preserve spatial orientation of specimens from the operating room into the paraffin block and onto the slide. Radio frequency identification tags link tissue to a patient encounter and provide chain of custody tracking from collection onward. Six United States patents are cited on the tissue technology alone. The second is grossing. BxCamera applies models at the grossing station to standardise measurement and description and document specimens automatically, addressing manual transcription between the bench and the laboratory system. The third is software and it carries the strongest credential on the record. Viewer+ received FDA 510(k) clearance for primary clinical diagnosis in March 2025 under number K242244. That is the distinction that separates this from most of the lane: a United States pathologist can sign out primary diagnoses on these images, where several neighbouring records are research use only or signal their status with an asterisk. BxLink is the combined viewer and laboratory information system for laboratories replacing an existing system, and the company states plainly on every page that BxLink itself is not FDA approved for digital primary diagnosis, so the clearance attaches to the viewer rather than to the whole catalogue. The fourth is the marketplace. Rather than building diagnostic models, Lumea integrates them, with a partner marketplace covering artificial intelligence, molecular tests and scanners, and announced partnerships with Paige and with Valar Labs for bladder cancer treatment decisions, both separately indexed here. Molecular test ordering sits one click from the diagnostic workspace. Founded in Lehi, Utah by Dr Matthew Leavitt, a dermatologist, with co founder Dr Jared Szymanski, a board certified pathologist, both among the earliest practitioners to attempt a full clinical digital transition. Leavitt moved to a board role in 2026 and the company announced a chief executive transition the same year. Specialty focus is urology, gastroenterology and dermatology, with prostate the anchor. One thing a reader should weigh. The company is candid that specimen quality drives diagnostic accuracy and sells the products that improve it, so its clinical argument and its commercial interest point the same way, which is not a criticism and is worth naming.

Pramana sits one step upstream of every other record in this lane. PathAI, Paige, Ibex, Aignostics and the rest analyse whole slide images. Pramana makes them. It builds autonomous whole slide imaging scanners and applies models during acquisition rather than after it, which makes this the only record in the pathology category where the artificial intelligence runs before a pathologist ever sees anything. The technical claim is hardware and software co designed together. Scanners perform fast focus sampling and dynamically calculate the z plane of the tissue, replicating the fine focus action of an optical microscope, and make inline decisions based on tissue type, thickness and slide artifacts such as annotations and debris. Edge models execute feature detection, quantification and classification in real time during the scan, so results are available the moment scanning completes rather than in a later processing pass. Quality assurance runs inline: each slide is annotated in real time for focus, stitching, bubbles, folds and other detectable errors, abstracted into tile based feature overlays and optionally a numeric quality metric, with autonomous rescanning when the scanner judges its own output inadequate. The company holds granted United States patents on the approach. Two product lines exist. A high throughput configuration handles routine and large caseloads, with a single scanning cluster stated at more than 1,000 slides a day. A desktop scanner takes four manually loaded slides and is positioned for labs entering digital pathology, satellite sites, teaching institutions and tumour boards. Sample coverage spans anatomic pathology, cytopathology, hematopathology, clinical pathology and microbiology, in brightfield. Alongside the hardware the company sells Digital Pathology as a Service, in which an institution sends glass slides and receives quality assured images without buying scanners or hiring staff to run them. That model produced the strongest evidence on this record. Mayo Clinic engaged the company in 2021 to evaluate throughput and quality, then awarded a multi million slide archival digitisation contract through a competitive process. The published result: 23,916 slides digitised over 30 days by a single human operator, roughly 800 a day, drawn from a tissue archive spanning the 1950s to the present, with no cleaning or preparatory steps, each slide annotated in real time by on scanner quality models. Founded in 2021 in Cambridge, Massachusetts by nference, a health data analytics company, with Matrix Capital Management named among investors. The company has since been acquired by Evident, the life science imaging business formerly part of Olympus, and the brand continues to be sold under its own name as the Pramana HT and Pramana M scanners, which is why it is enrolled rather than treated as absorbed. One regulatory fact belongs at the top rather than buried. The scanners are CE marked under the European in vitro diagnostic regulation and licensed by Health Canada, and in the United States they are research use only with a 510(k) submission pending. A United States laboratory cannot use these images for primary diagnosis today, and the company states that plainly on its product pages rather than obscuring it.

Mindray TE Air is indexed as a product, on the same basis as Vscan Air and Philips Lumify, and it sits closer to the membership boundary of this index than any other record in the handheld cluster. That is worth stating at the top rather than burying, because a reader comparing grades should know that this device is admitted for a thinner set of models than its neighbours carry. The series has two wireless probes. The e5M is a two in one whole body scanner combining convex and linear modes in a single housing, with more than 20 presets across abdomen, small organ, vascular, obstetrics, gynaecology and FAST, 22 exam types, scanning depth to 40 cm and roughly 120 minutes of battery. The i3P is a phased array with software based beam steering aimed at emergency and critical care cardiac work, and it is unusual in the cluster for being usable both as a mobile probe and as a transducer on the manufacturer's own trolley system, which turns one purchase into two deployment models. Both are rated IP68 and fully immersible for high level disinfection, both charge from empty to 90 percent in about 35 minutes, and both run through an application on an iOS or Android device the customer already owns. Imaging rests on the manufacturer's eWave platform and second generation single crystal transducer technology. The intelligence is narrow and mostly clerical. Scene recognition detects anatomy and switches and optimises presets automatically between abdomen, thyroid and carotid. iTouch+ performs one click image optimisation. PW Auto Calc traces a pulsed wave spectrum automatically and returns the standard velocity and resistance indices without manual measurement. Smart Bladder computes bladder volume from three automatically recognised diameters. These are real recognition models doing real work, and none of them produces a clinical finding. The richer tool set the manufacturer markets across its wider ultrasound line, covering B line counting, velocity time integral, inferior vena cava, fetal heart rate and automatic ejection fraction, runs on the trolley and portable systems rather than on this handheld, although an i3P docked to the trolley system reaches them. Where this product genuinely leads the cluster is commercial posture. Both probes are sold outright through the manufacturer's own online store with no subscription and an explicit commitment to no recurring fees, a standard three year warranty on the transducer and one year on accessories, published support hours, and a try before you buy demonstration programme. Against neighbours that gate intelligence, storage or imaging interchange behind annual tiers, buying the thing once and owning it is a materially different proposition and the manufacturer says so plainly rather than leaving a buyer to work it out. The manufacturer is headquartered in Shenzhen, China, with North American operations in Mahwah, New Jersey, and has been building medical devices for more than 30 years across patient monitoring, anaesthesia and ultrasound. Two things a reader should weigh. The published evidence base evaluates image quality rather than the models: independent comparative work rates this device well against cart systems and against other handhelds, and no validation of the recognition or measurement features was located, with the 2024 clearance summary recording that clinical studies were not required to support substantial equivalence. And some of the smart tools are sold as one time optional upgrades whose prices could not be located, so the no fees claim holds for the base device and is not the whole picture.

Philips Lumify is indexed as a product, on the same basis as Vscan Air. Royal Philips is far too broad to grade against these axes, so the assessment covers Lumify and the software that runs on it rather than the parent's wider portfolio. The form factor is the oldest idea in this cluster and still the most frugal. Lumify is a cabled transducer that plugs into a smart device the customer already owns, over USB on Android or Lightning on Apple hardware, and the app is downloaded from the ordinary consumer stores. There is no proprietary tablet, no wireless pairing and no battery in the probe, which is why scanning runs to roughly 7.5 hours on a suitable Android device where wireless competitors are measured in tens of minutes. Three broadband transducers cover the range: S4-1 phased array, C5-2 curved array and L12-4 linear. Fourteen presets include abdominal, cardiac, lung, FAST, musculoskeletal, obstetric and, more recently, ocular. Pulse wave Doppler arrived in 2022, adding hemodynamic quantification to what had been a 2D and colour device. Tissue Harmonic Imaging, SonoCT and xRes carry over from the cart line. Lumify was introduced in 2015. Two artificial intelligence features ship, both narrow and both branded. Auto B-line Quantification counts B lines automatically frame by frame during a lung exam and reports the maximum per zone against a guided 12 point protocol with zone by zone labelling. It was cleared in two stages, a counting algorithm first and then automated merged B lines in June 2023 across all three transducers. Auto EF calculates left ventricular ejection fraction from a single apical four chamber view with no manual editing, positioned explicitly as standardising quantification across users of varying experience. The regulatory paperwork is more revealing than the marketing, which is unusual and to the vendor's credit. The clearance summary for Auto EF identifies the underlying model as the LVivo EF algorithm developed by DiA, naming the outside supplier in a public document. The B lines summaries describe the counting mechanism, the dataset construction across lung zones and the ground truth method, which was agreement against a clinician majority with a pre defined success threshold. The lung work was developed under a partnership with the United States Biomedical Advanced Research and Development Authority, and the 2023 clearance was counted as the 74th authorisation supported under that programme, so a buyer can see that public money helped build the feature. Tele ultrasound runs through Reacts, a platform from Innovative Imaging Technologies integrated so a remote colleague can see the live scan and the device camera at once and the clinician controls what is shared. The device turns up in genuinely austere settings, including a Philips Foundation programme in Kenya training village midwives to perform antenatal screening with radiologist support at a distance. Three things a reader should weigh. Both artificial intelligence features are Android only, so a buyer standardised on Apple hardware gets an excellent scanner with no models on it, and that restriction is not prominent in the marketing. Pricing is the least legible in this cluster, with no published United States figure and third party signals that disagree by roughly a factor of two. And the published evidence for the two shipped models is thinner than for the cluster leaders, resting mainly on the clearance summaries rather than on independent trials.

Vscan Air is indexed as a product rather than as a company. GE HealthCare is far too broad to grade against these axes, so this record follows the Optum Integrity One precedent: the qualifying product line is assessed on its own terms and the parent is named. Everything below concerns Vscan Air and the software sold on it, not GE HealthCare's wider portfolio. The device is a wireless dual probe that pairs to a phone or tablet and fits in a coat pocket. Two configurations exist. The CL couples a convex and a linear transducer for abdominal, obstetric and deeper imaging. The SL couples a sector phased array and a linear transducer for cardiac, lung, vascular access and musculoskeletal work. B mode, M mode, colour Doppler and pulsed wave Doppler ship with the probe and function without any subscription, the probe is built to survive drops and rain, and scan time runs to roughly 50 minutes. Vscan Air launched in 2021, the current generation of a handheld line GE began with Vscan in 2010. The intelligence arrived by acquisition. GE HealthCare bought Caption Health in 2023 and brought Caption AI to Vscan Air SL in April 2024. It has two parts. Caption Guidance gives real time prescriptive instruction on how to manoeuvre the probe toward standard echocardiographic views and captures automatically once quality is reached. Caption Interpretation AutoEF calculates left ventricular ejection fraction from one or any combination of three views without manual endocardial border tracing, and the vendor states the calculation grows more accurate as each additional view is acquired. That software carries the strongest regulatory credential in this cluster. Caption Guidance was authorised through the De Novo pathway in February 2020 as the first artificial intelligence permitted to guide the acquisition of medical images, which means it created a device classification rather than matching an existing predicate. A separate expedited clearance followed in May 2020 for frontline pandemic use. The pivotal evidence is correspondingly strong and it is public. Published in JAMA Cardiology in 2021 from a registered trial, eight nurses with no prior ultrasound experience each scanned 30 patients across two hospitals, paired against sonographers using the same hardware without the software, with five independently trained echocardiographers blindly evaluating every acquisition. Images were of diagnostic quality for left ventricular size and function in 98.8 percent of patients, right ventricular size and function in 92.5 percent, and pericardial effusion in 98.8 percent, with at least 92.5 percent agreement on the corresponding diagnostic assessments. Results were reported as consistent across body mass index, sex and race, which is subgroup reporting almost no vendor in this index publishes. Several authors were employees of the company whose product was under test, and that is recorded here rather than passed on unqualified. Three things a reader should weigh. The intelligence is an option rather than a property of the device: it is cardiac only, sold separately, available on the SL and not the CL, and explicitly not available in every country. Interoperability follows the same pattern, with imaging interchange and cloud storage sitting behind a separate paid tier rather than shipping with the probe. And the published terms state that GE HealthCare may collect, derive from and use non personal data related to its products and services for research, development and product improvement, and that it owns the resulting rights while undertaking not to sell the data or identify the customer without consent. That clause is disclosed rather than buried, which is to its credit, and what counts as non personal data is not defined anywhere located.

EchoNous sits between the two poles of this cluster. Butterfly Network puts a single semiconductor probe against the whole body and Clarius sells a range of purpose tuned wireless scanners. EchoNous built Kosmos to argue that a handheld need not concede performance to a cart at all, and the claim rests on hardware rather than software: proprietary piezoelectric transducers, proprietary application specific circuits, and continuous wave Doppler, which the company states no other handheld offers. Continuous wave Doppler is what allows valve gradients and pressure calculations at the bedside, and it is the reason the device is positioned against cart systems rather than against pocket scanners. The artificial intelligence is a set of workflow models rather than a diagnostic one. AI FAST labels anatomy and identifies views in real time, an assisted ejection fraction workflow produces an automated left ventricular measurement, Auto Preset switches the exam preset as the operator moves between abdomen, lung and heart, and Auto Doppler positions the sample gate on the valve the clinician wants to interrogate. A February 2026 release added cleared obstetric biometry and billable vascular workflows. A June 2026 release added Vascular Auto Flow for fistula monitoring in dialysis patients, tricuspid valve Doppler calculations, and support for DICOMweb. Two third party models are offered on the platform and named openly: Us2.ai for automated echocardiography reports and 19Labs for tele ultrasound streaming. The evidence base is the strongest in this part of the index and most of it is not the company's own. Independent groups have validated the automated ejection fraction against cart based echocardiography in a multicentre Japanese study, against cardiac magnetic resonance in an Italian single centre cohort, in a diagnostic accuracy study published in npj Digital Medicine, and in a 115 patient cardio oncology cohort where staff without ultrasound expertise reached accuracies of 89 to 94 percent. The independent work also reports against the product's interest, the Japanese study finding that the automated system tended to underestimate ventricular volumes. The company separately publishes a prospective 78 patient study adjudicated blind by echocardiography core laboratories at two academic centres, which is well constructed and is the vendor's own. Data handling is architectural rather than contractual, and unusually clear. The products privacy policy states that protected health information is accessed only locally on the device, that only device identifiers and crash logs are transmitted, that the transmitted data contains no protected health information, and that EchoNous does not access, collect or disclose patient data. A Chief Privacy Officer is named. Scanning works offline, and a network is needed only to register a transducer, export to an imaging destination, or update software. The company was founded in Redmond, Washington by Kevin Goodwin, who had earlier founded SonoSite and shipped the first point of care ultrasound device in 1999, and by Dr Niko Pagoulatos. It began as Signostics, a bladder scanner business, and renamed itself EchoNous, meaning intelligent sound. Its own account dates the founding to 2016, while its corporate registration and site footer point to 2015. Privately held, backed principally by KKR with later financing from Kennedy Lewis, roughly $194M raised across seven rounds. Kosmos is sold in more than 70 countries and carries a five year warranty. Two things a reader should weigh. The published security posture is the weakest in this cluster, with no audited certification, trust centre or vulnerability disclosure policy located for a networked device sold into hospitals. And commercial disclosure is thin against its own competitors, with a single configuration ceiling published and no statement of what recurring cost, if any, a buyer carries.

Exo, pronounced echo, is the third handheld ultrasound approach in this index and the one that leans hardest on the software half. The company describes itself as a medical imaging software and devices company, in that order, and its silicon takes a middle path between the two competitors already graded here: a piezoelectric micromachined transducer built on silicon, blending the imaging behaviour of piezoelectric crystals with the cost structure of a chip. The Exo Iris device received clearance in 2021 with imaging modes and indications added the following year, and launched commercially in September 2023 at a starting price of 3,500 dollars. The artificial intelligence portfolio is the deepest in this cluster. By June 2025 the company reported 14 cleared indicators embedded in the device, spanning heart failure including reduced ejection fraction, cardiac hypertrophy, cardiomyopathies, valvular disease, pneumonia and pulmonary embolism, alongside bladder, hip and thyroid applications. Two things separate this from measurement automation. The indicators detect findings rather than only measuring structures, and in June 2025 the company cleared what it described as the first artificial intelligence for detecting pleural effusion and consolidation or atelectasis, stating that it showed superiority to clinicians alone. Separately, SweepAI evaluates image quality continuously while the operator sweeps and signals when enough diagnostic information has been captured, and is itself cleared for cardiac and lung use. Exo Works is the workflow half, launched in March 2022, handling documentation, billing, quality assurance and education for point of care ultrasound programmes. Its distinguishing property is that it is not tied to the company's own hardware: it is described as integrating with nearly any point of care ultrasound device and with common hospital record and imaging archive systems, reachable from a phone, tablet or browser. Wellstar MCG Health, formerly Augusta University Health, implemented it across its health system. Security disclosure is the strongest in this cluster and among the strongest in the index. Exo Works earned risk based two year certification under the healthcare assurance framework and completed an audited report at the operating effectiveness level in 2023, the company operates a public trust centre naming those alongside information security management certification, and it states that business continuity plans are validated through those same external audits. Roughly 428 million dollars raised across multiple rounds, most recently in May 2025, with about 192 employees as of March 2026. Led by co founder and chief executive Sandeep Akkaraju, headquartered in Santa Clara, California. Two things a reader should weigh. A vendor stating that its detection model outperforms clinicians alone is making the strongest comparative claim in this category, and no published study, accuracy figure or effect size supporting it was located outside the regulatory process. And the recurring commercial terms are undisclosed: a starting device price is published and nothing describing subscription, warranty or workflow software pricing was found.

Clarius Mobile Health takes the opposite approach to Butterfly Network on the same problem. Where Butterfly puts one semiconductor probe against the whole body, Clarius sells a range of wireless scanners each tuned to a purpose, six models in the current high definition third generation line covering full body, high frequency musculoskeletal and small parts, curved abdominal and obstetric, a dual array model, and an endocavity scanner for urology and women's health. Each connects over its own wireless link to an iOS or Android device, weighs between roughly 280 and 330 grams, and is sealed for full immersion during disinfection. Knobs and buttons were replaced with touch controls, voice control and automation. The artificial intelligence is a model portfolio rather than a feature. The company received clearance in February 2023 for what it described as the first artificial intelligence application cleared for musculoskeletal ultrasound, automatically identifying and measuring tendons in the foot, ankle and knee. In June 2024 it cleared a fetal biometry tool as its eighth model, automatically placing calipers and estimating fetal age, weight and growth intervals, developed on more than 30,000 de identified fetal ultrasound images and aimed explicitly at midwives, nurses and other new ultrasound users in resource limited settings. A prostate model is available in approved regions only. Measurements produced by these tools appear on screen and can be added to the patient record from the application. Commercial disclosure is the most complete encountered in this index. Scanners are priced publicly from roughly 2,995 dollars, membership is listed at 595 dollars a year with a lifetime licence alternative that varies by region, a three year warranty extendable to five is stated, a sixty day return policy is offered and accessory prices are published. Crucially the probe continues to function without a membership; the membership unlocks cloud and local study storage, advanced models, teleguidance and imaging interchange in the standard medical format. That is a materially different bargain from a device that stops saving studies when a subscription lapses. Technical disclosure extends to security parameters, with transport encryption and pairing encryption specified on the product pages alongside a protected health information removal feature and a statement that such data is stored in a compliant manner. The company reports scanners in use across more than 90 countries and, as of 2023, three million high definition scans performed. Privately held, led by president and chief executive Ohad Arazi, headquartered in Vancouver, British Columbia. Two things a reader should weigh. The specialty scanner strategy delivers depth per indication and multiplies cost for an organisation needing several, which is precisely the comparison a buyer should run against a single whole body probe. And no named institutional deployment with a quantified outcome was located, so adoption is evidenced by scan counts and country reach rather than by customer results.

Butterfly Network replaced the piezoelectric crystals inside an ultrasound probe with a silicon chip, and everything else about the company follows from that. A single handheld device images the whole body where conventional systems need several specialised probes, it connects to a phone or tablet, and because the imaging is done in software on general purpose silicon, new capability can be shipped as a cloud delivered update to devices already in clinicians' hands. The current generation is the iQ3, cleared in January 2024 and carrying a European conformity mark, with the earlier iQ+ still sold at a lower price. The artificial intelligence sits in three distinct layers and they are worth separating. The company's own tools assist acquisition and measurement, and in the first quarter of 2026 it became the first company to receive clearance for a blind sweep tool, which estimates fetal gestational age in under two minutes from a sweep that does not require the operator to know how to obtain the standard views. Compass AI is a separately licensed enterprise workflow platform, relaunched in November 2025, addressing documentation, compliance and billing for point of care ultrasound programmes; the company closed its first seven figure total contract value deal for it in early 2026. Butterfly Garden is a partner ecosystem, at 30 partners as of the first quarter of 2026, through which third party developers deliver their own applications on Butterfly hardware, four of them holding their own clearances and one holding a breakthrough designation. A separate line, Butterfly Embedded, licenses the underlying chip technology to other companies, nine as of April 2026. This record is at company level rather than product level. The index rejected Hologic at company level because a portfolio spanning diagnostics, surgical, skeletal health and mammography could not be graded coherently on these axes, and indexed its imaging software line instead. That reasoning does not transfer here: Butterfly is a single probe platform with one cloud and one software line around it. Commercially it is a small public company. First quarter 2026 revenue was 26.5 million dollars, up 25 percent, split for the first time into 20.8 million of core revenue covering probes, software and services and 5.7 million of embedded licensing. Cash stood at 138 million dollars against a quarterly burn of 12.5 million. Headquartered in Burlington, Massachusetts. Buyers span hospitals and health systems, medical schools running one probe per student programmes including Indiana University School of Medicine, veterinary practices, global health programmes and, from 2026, home and community care. The University of Rochester reported a 116 percent increase in point of care ultrasound revenue after a systemwide deployment. Two things a reader should weigh. Device prices and membership tiers are published, which is rare in this index, but a membership is required to activate the device and lapsing drops the probe to live view only, with no study saving, no advanced modes and no artificial intelligence, so for documented clinical use the subscription is effectively permanent. And imaging interchange in the standard medical format is not included in any membership tier and is purchased separately.

Nanowear weaves the sensors into the clothing. SimpleSense is a gender neutral, size adjustable undergarment built from patented cloth based nanosensors, capturing electrophysiological, hemodynamic, acoustic, metabolic and activity signals simultaneously and time synchronously, and feeding a deep learning platform that turns them into diagnostics. The company describes capturing more than 100 million data points per patient per day across cardiac, pulmonary and circulatory biomarkers, and positions the garment as replacing several separate instruments a clinician would otherwise use in sequence. Regulatory standing is the strongest element and includes one clearance type that matters more than its number. Four United States clearances span 2016, 2020, 2021 and January 2024. The 2021 clearance was software only, establishing standalone artificial intelligence and deep learning algorithms as a medical device in their own right rather than as an accessory to hardware. The 2024 clearance covered a cuffless continuous blood pressure diagnostic built on a four decision tree algorithmic model, validated across three study arms with training and validation performed in independent geographies and in demographic populations described as mirroring the most recent national census. The company publishes its indication for use, which is rare enough in this index to be worth stating plainly, and a reader should compare it against the marketing. The published indication covers use at home or in a healthcare facility, under the direction of a licensed medical professional, to record, display and store two leads of electrocardiogram, respiration rate measured through thoracic impedance, heart sounds, and activity including posture. That is a narrower and more precise claim than a garment capturing 85 or more biomarkers and replacing a stethoscope, a Holter monitor, a capnograph and a blood pressure cuff. Both statements come from the company; the cleared one is the one that binds. A dedicated security page exists naming Amazon Web Services as the host and linking a privacy notice, which again is more than most vendors here provide. Founded in 2014 and headquartered in New York with research operations in Berkeley and University Park, led by co founder and chief executive Venk Varadan. Intellectual property spans 13 awarded and 12 pending patents covering the nanotechnology, sensor manufacturing, the wearable, the software platform, the ingestion pipeline and the algorithms. Reported funding totals vary widely across sources and the chief executive has publicly stepped back from pursuing venture capital, so no figure is asserted here. Recent activity includes a licensing and data partnership ingesting continuous glucose readings from Dexcom and an integration initiative with blood collection patches. No pricing of any kind was located.

DermaSensor is a handheld instrument that a family doctor points at a suspicious mole. It uses elastic scattering spectroscopy to record how light scatters through tissue beneath the lesion, and a proprietary algorithm converts that optical signal into a risk result displayed on the device screen within seconds. The indication is narrow and deliberate: use by non dermatologist physicians, on lesions raising concern for melanoma, basal cell carcinoma or squamous cell carcinoma, in patients aged 40 and above. The regulatory milestone is the strongest in this index. On 17 January 2024 the device received De Novo authorisation, having previously held Breakthrough Device designation, making it the first artificial intelligence enabled device authorised for skin cancer detection in the primary care setting. De Novo is the harder route because no predicate device exists, so the pathway creates a new classification rather than borrowing one. It is also CE marked. The evidence behind it is a genuine clinical trial programme. Ten studies enrolled more than 1,300 subjects across more than 30 sites with over 2,000 pathology verified lesions. The pivotal DERM-SUCCESS study was international, multicentre, prospective and blinded, running at 22 sites with 30 primary care physicians across 1,005 patients and 1,579 lesions. Three separate multi reader multi case studies involving more than 280 primary care physicians measured what actually matters, which is whether the device changes physician behaviour: aided physicians correctly referred 91.4 percent of cancers against 82.0 percent unaided. The operating characteristics are published, and a buyer needs both halves of them. Sensitivity was 96.3 percent across common skin cancers, standalone melanoma sensitivity 90.2 percent, negative predictive value 98.1 percent for melanoma and 96.6 percent overall. Specificity was 20.7 percent. That last figure is the operational reality of the device and it appears far less prominently in company material than the sensitivity does: roughly four in five benign lesions will return a positive result. The device is built to avoid missing cancers, and it pays for that with referrals. One disclosure deserves specific credit. The device is authorised across all Fitzpatrick skin types, clinical studies included patients across the full range, and performance is stated as consistent regardless of skin pigmentation. Skin tone is the single most documented failure mode in dermatology artificial intelligence, and few products address it with regulatory backing. The authorised algorithm is also locked and cannot be changed without new studies and new authorisation. Labelling is explicit about what this is not: not a screening tool, not a sole diagnostic criterion, and not intended to confirm a diagnosis. Based in Miami. Commercial launch came in mid 2024, with more than 20,000 lesions scanned and hundreds of physicians using the device by late 2025. A 16 million dollar Series B closed in October 2025 taking total investment to 43 million. Commercially it is sold as a usage based subscription with a one time device setup and activation fee.

icometrix measures the brain. Its icobrain software automatically detects, segments and quantifies brain structures and lesions from magnetic resonance and computed tomography images, then reports those measurements against an age and gender matched reference population so a clinician can see whether a given brain differs from expectation and whether it is changing over time. Longitudinal comparison across scans acquired at different times is patented and is the capability the company was built around. Coverage is unusually wide for imaging artificial intelligence. Modules address multiple sclerosis, dementia and Alzheimer's disease, amyloid related imaging abnormality monitoring, traumatic brain injury, stroke, epilepsy, brain tumours and Parkinson's disease, with a portfolio described as eight regulatory approved solutions. Alongside icobrain sit icobridge, which connects magnetic resonance scanners, picture archiving systems and record systems and handles transfer, report generation and dashboards, and icompanion, a patient facing application for people with multiple sclerosis. The regulatory record runs a decade. First United States clearance came in September 2016, European marking followed under the newer medical device regulation pathway, and in June 2026 icobrain aria was cleared as the first artificial intelligence software to detect, measure and grade amyloid related imaging abnormalities, the serious adverse effect associated with new anti amyloid Alzheimer's therapies. The company describes that clearance as the first computer aided detection and diagnosis solution authorised in neuroradiology, a category held to markedly higher evidence standards than quantification alone. In the United Kingdom the multiple sclerosis measures received a Medtech Innovation Briefing from the national health technology assessment body in April 2022. In the United States the service qualifies for reimbursement under an established procedure code for three dimensional post processing. Ownership changed in 2026: icometrix is now a GE HealthCare company. That is the most consequential fact on this record for a prospective buyer, and it cuts both ways. It brings distribution, capital and an installed scanner base, and it raises the questions any acquisition raises about roadmap independence, pricing under a larger vendor's commercial structure, and whether neutrality toward competing scanner manufacturers persists. The brand, the products and the site remain under their own name, which is why this is indexed as its own record. Founded in 2011 as a spinout in Leuven, Belgium, with United States operations established in the Boston area in 2016 and a further presence in New Jersey. Output is delivered as colour coded segmentations in DICOM format, concise reports carrying normative reference data, and prepopulated reporting templates. Data handling is stated to comply with United States health privacy law and European data protection law, with encrypted transfer, secure storage and controlled access. No pricing of any kind was located, and no customer count, deployment scale figure or named health system reference was found in public material.

Optellum scores whether a lung nodule is cancer. Virtual Nodule Clinic identifies, triages and tracks patients with pulmonary nodules, and its Lung Cancer Prediction AI computes a malignancy risk score from full patterns of three dimensional pixels in an ordinary computed tomography scan, using a convolutional neural network trained as a radiomics based digital biomarker. The clinical problem it addresses is specific and large: roughly two million incidental lung nodules are found each year in the United States and a substantial share of those patients never receive follow up, while small tumours treated early carry survival rates far above late stage disease. The company is building a wider platform, LungOS, on what it describes as the first thorax computed tomography foundation model, announced in August 2025. Regulatory standing spans four jurisdictions. United States clearance came in March 2021, the first for artificial intelligence decision support in lung cancer diagnosis, followed by European medical device regulation marking, United Kingdom marking, and Australian class IIb approval in February 2026. The reimbursement position is what sets this record apart and is rare enough in this index to state plainly. Two temporary procedure codes took effect on 1 July 2022 covering quantitative computed tomography tissue characterisation, one standalone and one alongside a concurrent scan. In the hospital outpatient setting the standalone code sits in a new technology payment classification at a rate of roughly 600 to 700 dollars per use, paid at the full rate without multiple procedure discounting. The company maintains a dedicated reimbursement page explaining the mechanics, and it is candid about the limits: these are temporary category codes carrying no relative value units, claims may need supporting documentation to establish medical necessity, and regional contractors decide case by case. Evidence runs from algorithm validation through to health economics. External validation appeared in Thorax in 2020 and risk stratification accuracy in the American Journal of Respiratory and Critical Care Medicine the same year. Real world impact on time to diagnosis and follow up rates was published in BMJ Open Respiratory Research in December 2025 and presented at a European oncology congress. In March 2026 a Vanderbilt led lifetime payer perspective analysis reported the approach cost effective, and in June 2026 the company was awarded competitive national research funding for a multi site pilot in the English health service. Deployment passed 250 clinical sites and three million scans analysed by June 2026, with named customers including the University of Pennsylvania Health System, Vanderbilt University Medical Center, Oxford University Hospitals and Tanner Health. Security is certified against the 2022 revision of the international information security management standard, achieved in August 2024, with the scope enumerated across design, development, manufacture, sales and support, and the company runs a public trust centre. Headquartered at the Oxford Centre for Innovation with a United States office in the Texas Medical Center in Houston. A Series B closed in January 2026 adding new strategic investors.

Truveta is a collective of 30 United States health systems that pooled their patient records into one research dataset and own the company that runs it. Founded in 2020 and based in Bellevue, Washington, led by co founder and chief executive Terry Myerson, it holds de identified electronic health record data representing more than 120 million patients. Members include Providence, Advocate Health, Trinity Health, Northwell Health, CommonSpirit Health, Tenet Healthcare, Henry Ford Health, Ochsner Health, MedStar Health, Memorial Hermann and twenty others. The artificial intelligence is the Truveta Language Model, described as a large language multi modal model that normalises billions of data points from thirty different record estates into a single consistent structure, running on Microsoft Azure. Microsoft has invested in the company. Normalisation is the hard part of this business: the same diagnosis, drug and laboratory result are recorded differently in every system, and research is only possible once they agree. The company positions the result as regulatory grade safety and effectiveness data that can replace slow and expensive clinical trials and registries, and published work using it spans cardiovascular, neurology, oncology and metabolic research, including studies of GLP-1 medicines and methodological comparisons between claims and record data. In January 2025 members launched the Truveta Genome Project with the Regeneron Genetics Center and Illumina, which will sequence the exomes of an initial ten million volunteers and is described as more than ten times the scale of previous efforts, with explicit representation across ancestries, ethnicities, sex and social drivers of health as a design goal. Consent is obtained at the point of care to use leftover biospecimens from routine laboratory tests, which are sent for sequencing and linked to de identified records, with remaining material stored for future multi omics work. Health systems, Regeneron and Illumina invested 320 million dollars in preferred equity at a valuation above one billion dollars, Regeneron contributing 119.5 million and Illumina 20 million.

Ultromics reads a routine echocardiogram and detects disease a human reader cannot see in it. A spin out from the University of Oxford founded in 2017 by chief executive Ross Upton, working with Professor Paul Leeson at Oxford and Dr Patricia Pellikka at Mayo Clinic, it has built the EchoGo platform around the idea of identifying disease directly rather than automating measurements. It holds four Food and Drug Administration clearances and two Breakthrough Device designations. EchoGo Heart Failure, cleared in 2022, aids detection of heart failure with preserved ejection fraction, a common form that is difficult to diagnose. EchoGo Amyloidosis, cleared in November 2024 under K240860, was the first artificial intelligence tool cleared for cardiac amyloidosis and the first device enrolled in the agency's Total Product Lifecycle Advisory Programme to reach marketing authorisation, from a pilot of fifteen breakthrough cardiovascular devices. The amyloidosis model works from a single routinely acquired apical four chamber videoclip, which is materially less input than the usual pathway of electrocardiography, cardiac magnetic resonance, scintigraphy and sometimes biopsy. A multi centre international study in the European Heart Journal, run with Mayo Clinic and investigators at the University of Chicago Medicine across more than 18 sites, validated it on an external cohort of 2,719 patients with a 22 percent prevalence of the disease, reporting an area under the curve of 0.93 with 85 percent sensitivity and 93 percent specificity across more than 12,500 cases. The company separately publishes the figures from clinical evaluation under intended use conditions in its clearance summary, 84.5 percent sensitivity and 89.7 percent specificity. Performance held across all major subtypes and distinguished the disease from conditions that mimic it, including hypertensive heart disease, heart failure with preserved ejection fraction and hypertrophic cardiomyopathy. Evidence for the heart failure product is cited in the 2025 American Society of Echocardiography diastology guidelines, and that product carries Medicare reimbursement through Category III code 0932T for outpatient use and a new technology add on payment for inpatient settings. More than 25 peer reviewed studies support the platform, which is in use at UChicago Medicine, Northwestern and City of Hope. Development collaborators include Pfizer and Janssen Biotech.

Veracyte builds genomic classifiers, each one a machine learned model over RNA whole transcriptome data, and it is the direct competitor to the artificial intelligence prostate tests indexed alongside it. Founded in 2008, based in South San Francisco with laboratories there and in San Diego, and listed on Nasdaq, it reported testing revenue of 135.8 million dollars in the fourth quarter of 2025, up 21 percent. The flagship is Decipher Prostate, a 22 gene classifier developed with machine learning that estimates the risk of metastasis and informs how intensively to treat. More than 300,000 patients have been tested since launch, over 100,000 of them in 2025 alone, with roughly 27,200 tests in the fourth quarter and a fifteenth consecutive quarter of volume growth above 20 percent. Market penetration is stated at about 33 percent. Its standing in the guidelines is the strongest of any record in this index. Decipher Prostate is the only gene expression test to reach Level I evidence and inclusion in the risk stratification table of the National Comprehensive Cancer Network guidelines for prostate cancer, and those guidelines uniquely recommend using its score to guide whether to add hormone therapy after prostatectomy, a recommendation resting on a Phase 3 randomised trial with a median of twelve years of follow up. Performance has been examined in more than 85 studies covering over 200,000 patients, and results have been linked to real world outcomes through the National Cancer Institute's SEER database. The classifier is currently under investigation in seven Phase 3 randomised trials sponsored by that institute. The wider portfolio uses the same method in other cancers: Decipher Bladder, a 219 gene classifier sorting tumours into five molecular subtypes; Afirma for thyroid nodules; Prosigna for breast cancer; Percepta for lung, including a nasal swab test whose trial has completed enrolment; and Envisia for interstitial lung disease, with lymphoma and renal tests in development alongside a tumour informed test for minimal residual disease. The company holds exclusive global access to the nCounter analysis system, which lets laboratories run its tests locally rather than shipping samples. HalioDx is among the businesses it has absorbed.

ScreenPoint Medical, based in Nijmegen in the Netherlands and led by chief executive Pieter Kroese, makes Transpara, breast artificial intelligence for mammography screening. It holds the strongest trial evidence of any vendor in this index. Transpara gives each examination a malignancy risk score from 1 to 10, calibrated so roughly a tenth of examinations fall in each score band, and adds marks on suspicious findings with regional risk scores for intermediate and high risk cases. The top one percent of risk, above a threshold of 9.8, is flagged in the image worklist as extra high risk. In the screening workflow that score decides how much human reading an examination receives: low and intermediate risk go to a single reader, high risk to two. That workflow was tested in a randomised controlled trial rather than asserted. The Mammography Screening with Artificial Intelligence trial ran inside the Swedish national screening programme across four sites in the southwest, randomising more than 105,000 women one to one between artificial intelligence supported screening and standard double reading, led by Kristina Lang of Lund University and registered as NCT04838756. The results were published in three stages. A clinical safety analysis in The Lancet Oncology in 2023 reported a 44 percent reduction in screen reading workload. A secondary analysis in The Lancet Digital Health in 2025 reported a 29 percent increase in cancer detection, 338 cancers among 53,043 participants, with no increase in false positives and more small, node negative invasive cancers detected. Final results in The Lancet in January 2026 addressed the endpoint that matters most, cancers appearing between screening rounds: a 12 percent reduction in the interval cancer rate meeting non inferiority, 27 percent fewer aggressive subtypes, sensitivity of 80.5 percent against 73.8 percent, and identical specificity at 98.5 percent. A separate paired non inferiority trial appeared in Nature Medicine in March 2026. Transpara is deployed in more than 30 countries with over 12 million mammograms processed. In April 2026 the company raised 14 million dollars from Insight Partners and Siemens Healthineers alongside 2 million in research grants.

Mirvie predicts complications of pregnancy months before they appear, from a blood sample rather than from the mother's characteristics. Founded in 2018 and based in South San Francisco, it combines cell free RNA transcriptomics with machine learning to read the molecular state of the placenta and the developing pregnancy. The first commercial product, Encompass, launched in 2025 and predicts preeclampsia risk between 17.5 and 22 weeks of gestation in pregnancies carrying no pre existing high risk conditions. The company reports that a low risk result carries a 99.7 percent probability of not developing preterm preeclampsia, and that the test identified 91 percent of pregnancies that went on to develop preterm preeclampsia among women aged 35 and over without pre existing risk factors. Encompass is sold as a package rather than a result alone, pairing the test with a preventive action plan and a virtual assistant. The evidence base is unusually substantial for a company of this age. A validation study published in Nature Communications in April 2025 drew on more than 9,000 pregnancies from the company sponsored multi centre Miracle of Life prospective study, identifying RNA signatures that distinguish severe from mild hypertensive disorders of pregnancy. Earlier work appeared in Nature on preeclampsia prediction and in the American Journal of Obstetrics and Gynecology on preterm birth, with research on fetal growth restriction presented at a maternal fetal medicine meeting. The platform is stated to have examined the molecular health of close to 11,000 pregnancies. The clinical argument is that existing practice identifies risk from maternal characteristics under national guidelines, that preeclampsia rates have nearly doubled in a decade to affect roughly one pregnancy in twelve, and that a molecular signal separates the pregnancies genuinely at risk from those merely resembling them. Where risk is identified, the established response is low dose aspirin and closer monitoring. The company's vice president of clinical development, Thomas McElrath, is a maternal fetal medicine physician at Brigham and Women's Hospital.

Eyenuk makes EyeArt, an autonomous artificial intelligence system that grades a retinal photograph and returns a diagnosis without any clinician reading the image. It is one of only three systems cleared by the Food and Drug Administration for diabetic retinopathy testing in the United States, alongside the already indexed Digital Diagnostics and AEYE Health, and it is based in Los Angeles. Clearance came in August 2020 under 510(k) K200667. EyeArt was the first cleared autonomous system able to detect both more than mild and vision threatening diabetic retinopathy in a single test, and the first to return a diagnostic output for each eye separately. Its indication is confined to adults with diabetes not previously diagnosed with more than mild disease. Results are returned at the point of care in under a minute. Two further regulatory positions distinguish it. Version 2.2.0 added clearance for the Topcon NW400 camera alongside two Canon models, making it the only cleared system usable with retinal cameras from different manufacturers rather than tied to one. And version 3.0 holds Class IIb CE marking under the European medical device regulation for three diseases from one exam: diabetic retinopathy including macular edema, age related macular degeneration, and glaucomatous optic nerve damage. It is the only system holding both that three disease European marking and United States clearance for diabetic retinopathy. It is also approved by Health Canada. In September 2025 Norway selected EyeArt as the artificial intelligence system for its national diabetic eye screening programme, following a competitive procurement run by the national purchasing organisation on behalf of the regional health authorities. Grading runs in under 30 seconds with no ophthalmologist review and results are written into the national electronic record. Other deployments include more than 25 centres in Italy, a German diabetes clinic, rural and remote screening in Canada, and Federally Qualified Health Centres in Delaware through a partnership with the American Academy of Ophthalmology. Founded by Kaushal Solanki; chief executive Gaurav Agarwal as of 2025.

Prenosis is a Chicago company whose Sepsis ImmunoScore was the first artificial intelligence diagnostic for sepsis ever granted marketing authorisation by the Food and Drug Administration, cleared through the De Novo pathway on 3 April 2024. Because De Novo creates a new device classification, that authorisation established the category a later competitor used as its predicate, which makes this record the regulatory origin point of the whole cleared sepsis segment. What separates it technically from the other deterioration products in this index is that it does not read the record alone. The score combines biological markers measured from a blood sample with clinical data drawn from the record, using up to 22 parameters, and returns a risk score placing the patient in one of four discrete risk categories. Those categories are tied to length of stay, in hospital mortality and escalation of care within 24 hours, meaning intensive care admission, mechanical ventilation or vasopressor use. The company states explicitly that it is not an alert system. The underlying asset is the Immunix platform and the biobank built on it: more than 100,000 blood samples from over 25,000 patients, assembled across a decade with ten partner hospitals and held in a biosafety level 2 laboratory in Chicago, paired with clinical data from those hospitals' records. The company describes this as the largest combined biological and clinical dataset in the world for acute care patients suspected of serious infection. Sepsis ImmunoScore is distributed commercially through a collaboration with Roche, appearing on the navify Algorithm Suite. In January 2026 the company announced 40 million dollars, comprising a 20 million dollar Series A led by PACE Healthcare Capital with the Labcorp Venture Fund and Carle Health, and a 20 million dollar federal contract from BARDA funding a randomised controlled trial of 800 patients with severe respiratory infections. Co founder and chief executive Bobby Reddy Jr. Founding year was not confirmed in this pass and is left blank.

Anumana builds neural network algorithms that read a standard electrocardiogram to detect disease the trace was never thought to reveal. It was founded in 2021 as a joint venture between Mayo Clinic and the health data company nference, and is based in Cambridge, Massachusetts. Mayo Clinic co founded the company and holds a financial interest in it, which the company discloses in its announcements. The premise is that an inexpensive, century old test contains signal beyond what a human reader can extract. The platform is stated to be built on more than 22 million patient records spanning more than 20 years, obtained through exclusive partnerships with academic medical centres, and the flagship low ejection fraction model is described as developed from roughly 2.9 million paired electrocardiogram and echocardiogram studies across more than 676,000 patients. Three algorithms have been cleared by the Food and Drug Administration. ECG-AI LEF detects low ejection fraction and is available in the United States and the European Union. ECG-AI PH, cleared March 2026, detects pulmonary hypertension and is the first such algorithm cleared for use with a standard 12 lead electrocardiogram. A cardiac amyloidosis algorithm was cleared in April 2026 and is stated to be the first and only one for that indication on a standard 12 lead trace. Several algorithms have held Breakthrough Device Designation, and the amyloidosis product was selected among the first 15 devices in the agency's Total Product Life Cycle Advisory Programme pilot. The company raised a 25.7 million dollar Series A led by its two founders alongside Matrix Capital Management, Matrix Partners and NTTVC, and acquired the cardiac electrophysiology data company NeuTrace in 2022. It runs algorithm development collaborations with Novartis, Johnson and Johnson and Pfizer.

Guardant Health is a publicly traded precision oncology company, listed on Nasdaq as GH, founded in 2012 and based in Palo Alto, California, led by co chief executives Helmy Eltoukhy and AmirAli Talasaz. It sells blood and tissue based cancer tests across four stages of care: screening the average risk population, selecting therapy in advanced disease, monitoring for recurrence, and supporting biopharmaceutical development. The therapy selection product is Guardant360. Guardant360 CDx was the first liquid biopsy approved by the Food and Drug Administration for comprehensive genomic profiling, and by January 2026 carried its 25th companion diagnostic indication. In May 2026 the agency approved Guardant360 Liquid CDx, which the company describes as the largest approved liquid biopsy panel, assessing a genomic footprint 100 times wider than the previous version and combining genomic with epigenomic profiling from a single blood draw. The seven companion diagnostic indications on the earlier test transferred to it. A separate Guardant360 Tissue product is a laboratory developed test run under the company's own clinical laboratory certification and is not approved by the agency, which is a distinction buyers frequently miss. The screening product is Shield, approved in July 2024 as the first blood test for primary colorectal cancer screening. It was granted Advanced Diagnostic Laboratory Test status by the Centers for Medicare and Medicaid Services, was added to the American Cancer Society colorectal cancer screening guidelines in 2026, and received a UnitedHealth Group coverage decision effective 1 August 2026. Guardant Reveal covers recurrence monitoring and holds Medicare coverage for colorectal cancer through the molecular diagnostics services programme. The company describes an artificial intelligence layer called the Smart Platform, and a branded capability called InfinityAI. More than one million blood tests have been performed.

Creyos, formerly Cambridge Brain Sciences and briefly Creyos Health, is a Toronto company selling digital cognitive and behavioural health assessment to clinicians. The platform administers twelve short computerised tasks, each mapped to a named cognitive domain covering memory, attention, reasoning, verbal ability and planning, and scores a patient against a normative database the company states holds more than 85,000 participants. Digitised versions of standard behavioural health questionnaires sit alongside the tasks, and a care planning capability was added in 2026. The tasks originate in three decades of research by Professor Adrian Owen, who built them at Cambridge, launched the web platform in 2009, and continued validating them at Western University's Brain and Mind Institute after winning a Canada Excellence Research Chair. The company states the tasks have been used in more than 400 peer reviewed studies. Applications span mild cognitive impairment and dementia screening, attention deficit assessment, concussion and traumatic brain injury, and research use. The company positions the product as a clinical decision support tool and describes the platform as registered with the FDA, which is a different and much weaker status than clearance.

Magentiq Eye is a Haifa company founded in 2014 by Dror Zur that builds real time computer aided detection for colonoscopy. Its product, Magentiq-Colo, registered with the FDA as the Magentiq Eye Automatic Polyp Detection System, takes the video feed out of the colonoscope, splits it into frames, analyses them with a deep learning model as the procedure is happening, and returns the video to the monitor with bounding boxes drawn around suspected polyps. The purpose is to reduce the proportion of adenomas an endoscopist walks past. The product carries a CE mark and Israeli approval from mid 2021 and an FDA clearance from July 2023, with an updated cleared version released in January 2026 adding endoscopic tool detection, and a separately CE marked feature set covering polyp size estimation and characterisation plus procedural quality metrics that the United States version does not include. Its evidence is unusually strong for this index: an international multicentre randomised tandem trial across ten centres in Europe, the United States and Israel, published in Lancet Digital Health in February 2024.

C the Signs is a London company founded by two NHS general practitioners, Dr Bhavagaya Bakshi and Dr Miles Payling, that identifies patients at risk of cancer during a primary care consultation. The platform combines electronic health record data with patient reported information to assess risk across more than 100 cancer types, predict likely tumour origin, and route the patient into an urgent, test first or non urgent pathway, with the vendor stating a result inside 60 seconds drawn from over 1,000 evidence based data points mapped against NICE and local guidance. It is integrated with EMIS, SystmOne and Vision, which between them cover essentially the whole English general practice software market, and assessments and safety netting are coded back into the patient record. It reports deployment across roughly 1,400 general practices and more than 70,000 patients with cancer detected. It is registered with the MHRA as a Class I medical device, which is a self certified classification rather than a reviewed authorisation, and the company has published its evaluations largely through oncology conference abstracts at ESMO, ASCO, AACR and an NCI symposium.

Digital Diagnostics, founded in Coralville, Iowa as IDx Technologies by retina specialist and computer engineer Michael Abramoff, MD, PhD, builds autonomous AI diagnostic systems. Its flagship product LumineticsCore, formerly IDx-DR, detects more than mild diabetic retinopathy including macular edema from retinal images and returns a diagnostic report at the point of care without any physician evaluation of the image. In April 2018 it became the first autonomous AI diagnostic system authorised by the FDA in any field of medicine, granted through the De Novo pathway as a Class II device after expedited review under the Breakthrough Devices programme. A 510(k) for the current version cleared in May 2021 on its own predecessor as predicate, carrying the original De Novo special controls forward. The company also markets DermSpot for skin, whose regulatory status was not established in this assessment. LumineticsCore is the reference case for autonomous diagnosis in this index: the model does not assist a clinician, it replaces the interpretation step, and the company states that the creator of the autonomous AI assumes liability for the diagnosis it produces.

Genomind pairs a pharmacogenetic laboratory test with software that turns the result into prescribing guidance, with a centre of gravity in mental health. The assay is a clinician ordered buccal swab genotyped by quantitative PCR across 26 to 27 genes, split between 11 that affect how a drug is metabolised and 15 that affect how the body responds to it, returning results in three to five days and covering more than 700 medications. The Precision Health Platform then integrates that genotype with the patient's current medication list to flag gene to drug and drug to drug interactions and propose alternatives. The company was founded in King of Prussia, Pennsylvania by Dr Ronald Dozoretz, sells to individuals, prescribers, long term care facilities, accountable care organisations, employers and health plans, holds a contract supporting testing for United States active duty service members, and licenses its reporting suite to other laboratories so that its interpretation layer reaches patients whose samples it never handled. What distinguishes this record from everything else in the category is what the company did with its own evidence. It sponsored and co authored a multicentre randomised controlled trial of its own test in major depressive disorder, blinded to both participants and raters, and the trial found no significant improvement in the primary efficacy outcome. The company continues to cite that trial on its own science page.

YouScript computes the cumulative effect of a patient's whole medication regimen together with their pharmacogenomic results, rather than checking drug pairs one at a time. Its founder, Kristine Ashcraft, makes the argument directly: American practice has relied on binary interaction alerting for decades, and binary alerting breaks down once a patient is on five or more medications, which now describes tens of millions of people. The patented engine models drug to drug interactions, drug to gene interactions and phenoconversion, where one drug alters how a patient metabolises another and effectively changes their genotype in practice, then returns severity coded guidance across four levels from change to no change alongside safer alternatives within the same drug class or indication. It draws on more than 19,000 high evidence references covering over 2,000 medications and integrates with Epic, Cerner, Allscripts and Telus Health as well as through standalone applications and APIs. The product was incubated for over a decade inside Genelex, a pharmacogenetic testing laboratory in Seattle, established as YouScript in 2016, acquired by Invitae in 2020, and sold to Aranscia in an all cash transaction announced in November 2023. It holds something rare in this category: a prospective randomised controlled trial with a rehospitalisation endpoint. It also markets itself as laboratory agnostic while having been owned by a testing business for essentially its entire existence.

Cytovale's IntelliSep is an FDA cleared in vitro diagnostic that assesses a patient's probability of sepsis by measuring the mechanical behaviour of their own white blood cells rather than by looking for a pathogen or a biochemical marker. It is indexed here rather than in inpatient monitoring because it is a point in time test performed on a blood sample, not continuous surveillance. The underlying observation is that when leukocytes become activated, as they do in sepsis, their biomechanics change: size, deformability, stiffness and behaviour under fluid stress all shift. The Cytovale System exploits this by taking 100 microlitres of whole blood, lysing the red cells and washing the leukocytes, then passing tens of thousands of individual cells through a microfluidic junction where hydrodynamic forces deform them. Ultra high resolution imaging captures each cell during that deformation at very high frame rates, and high throughput image analysis, computer vision and machine learning translate the resulting cell images into a single score. Results return in roughly eight to ten minutes. The output is the IntelliSep Index, a value from 0.1 to 10.0 stratified into three published bands: Band 1 from 0.1 to 4.9 indicating low probability of sepsis, Band 2 from 5.0 to 6.2 indicating intermediate probability, and Band 3 from 6.3 to 10.0 indicating high probability. The cleared indication is precise: adult patients with signs and symptoms of infection presenting to the emergency department, to aid early detection of sepsis with organ dysfunction manifesting within the first three days after testing, with results intended for use alongside clinical assessment and other laboratory findings. Clearance came under K220991 in December 2022, supported by the multicentre CV-SQuISH-ED clinical validation study whose national principal investigator was Hollis O'Neal MD of Our Lady of the Lake Regional Medical Center and LSU Health Sciences Center. The underlying science traces to deformability cytometry work by Dino Di Carlo at UCLA, who along with the Regents of the University of California holds a disclosed financial interest in the company. Cytovale is based in San Francisco, led by co founder and chief executive Ajay Shah, and raised a 100 million dollar Series D led by Sands Capital in October 2024 with participation from CPP Investments, Norwest Venture Partners, Global Health Investment Corporation and Breakout Ventures. Pricing is not published; the company has applied for a CPT Proprietary Laboratory Analyses code.

Eko Health puts cardiac detection AI inside the stethoscope. SENSORA is its enterprise platform: FDA cleared software that analyses simultaneous ECG and heart sound data captured by an Eko digital stethoscope during a routine exam, and flags low ejection fraction at or below 40 percent, atrial fibrillation, structural heart murmurs and normal sinus rhythm, while calculating intervals including heart rate, QRS duration and electromechanical activation time. Capture can be performed by medical assistants and nurses as part of intake, not only by physicians. The company is led by co founder and chief executive Connor Landgraf and holds a stack of clearances built up over a decade: its digital stethoscope in 2015, then algorithms for structural murmur and atrial fibrillation, the Duo combined ECG and stethoscope, and in 2024 the Low Ejection Fraction tool developed in collaboration with Mayo Clinic. In November 2024 the AMA granted SENSORA a Category III CPT code, 0962T. The evidence base is unusual for this index. A randomised controlled trial across more than 200 NHS primary care practices was published in The Lancet and is described as the largest AI cardiology RCT conducted. An independent validation in Circulation found the murmur algorithm doubled sensitivity for structural heart disease against an analogue stethoscope. A Lancet Digital Health study of over 1,000 patients addressed the low ejection fraction algorithm in primary care. The product is deployed across more than 100 UK clinics through the NHS and Imperial College London. Filed alongside AccurKardia, HeartSciences and Ceribell as a cleared device plus algorithm that detects disease from a physiological signal, rather than as surgical decision support.

Australian medical technology company, ASX listed as AYA, commercialising the Salix AI cloud platform for near real-time point-of-care assessment of coronary artery disease from CCTA. The platform is modular and each module carries its own regulatory status: Salix Coronary Anatomy was cleared in March 2025, Salix Coronary Plaque received FDA 510(k) clearance in August 2025 under K251837, and Salix Coronary Flow was completed with clinical data validation underway ahead of a further 510(k) submission. The plaque module sits inside the same user interface as the anatomy platform and was enabled in the live product immediately on clearance. The design emphasis is speed and self-sufficiency: assessments in under 10 minutes without switching systems, and explicitly no external reading teams validating scan data, so physicians retain direct control rather than waiting on a vendor-side processing service. That is a genuine architectural difference from Heartflow's analysis-service model. Plaque volume is computed by identifying voxels within target Hounsfield Unit ranges located between the lumen and outer vessel wall, and the product reports plaque features including low attenuation plaque, spotty calcification, positive remodeling and the napkin-ring sign, presented through a personalised 3D heart model. The algorithm was built from thousands of scans contributed by institutions in the US, Australia and Canada. Commercial deployment is live at Tanner Health across five hospitals generating fee-per-scan revenue, with Northeast Georgia Health and Cone Health integrating. The SAPPHIRE study is a retrospective multi-centre real-world study across six major US health systems including Piedmont Healthcare, running in three phases to evaluate the prognostic utility of a proprietary Plaque Dispersion Score, with a stated focus on coronary artery disease in women given that a large majority of women who die of coronary disease had no prior symptoms.

The regulatory originator of computerised cognitive testing in the United States. Cognivue holds a De Novo classification, DEN130033, validated against the St. Louis University Mental Status examination, which makes it the first FDA cleared computerized cognitive test and means it created the device category that later entrants such as BrainCheck and Linus Health were cleared into. The same relationship Viz.ai has to computer aided triage. The technology rests on adaptive psychophysics rather than digitised paper instruments: the test dynamically adapts as the patient progresses, calibrating to each individual's visual and motor abilities, and collects over 130,000 data points to produce a single clinical score. Two self-administered products share the cleared technology, Clarity, a 10 minute assessment covering memory, executive function and attention, discrimination and visuospatial domains plus two performance parameters, and Thrive, an abbreviated 5 minute screening covering three domains and designed for a busy office or pharmacy setting. Both are self-administered by the patient without a clinician proctor, which is the central operational difference from competitors and the basis of the company's claim to remove administrator bias and variability. Devices are calibrated identically across units to support consistency and retest reliability. The evidence base is substantial and independent: a published validation reported Cognivue as equally effective as the Montreal Cognitive Assessment with superior test-retest reliability, and the FOCUS study enrolled 452 participants across six US sites, comparing against the Repeatable Battery for the Assessment of Neuropsychological Status specifically to establish performance across age, education, sex, race and ethnicity strata. Products are indicated as adjunctive tools for evaluating cognitive function, explicitly not stand-alone diagnostics.

Digital cognitive assessment built on machine learning analysis of drawing and speech behaviour rather than on digitised test scoring, which is the distinction that separates it from most of this category. The flagship DCTclock analyses the entire process of drawing a clock, capturing temporal and spatial features of stylus manipulation across the whole drawing rather than scoring the finished picture, and extracts cognitive and motor metrics no paper version can produce. Digital Clock and Recall (DCR) adds immediate and delayed word recall to assess verbal memory, runs in about three minutes, and the LinusAD algorithm combines age, APOE status, drawing metrics, speech and acoustic features and stylus dynamics. The suite now exceeds a dozen assessments including a digital Trail Making Test Part B, a Digital Assessment of Cognition, gait and speech measures, and the electronic Person Specific Outcome Measure. Technology originated in over a decade of R&D at Lahey Hospital & Medical Center and MIT. The commercially important capability is biomarker prediction, which puts this product in a different business from cognitive screening: peer reviewed work found DCTclock significantly correlated with amyloid PET in cognitively normal individuals and outperforming the 30 minute Preclinical Alzheimer's Clinical Composite at distinguishing amyloid positive from amyloid negative, a Harvard Aging Brain Study longitudinal cohort of over 200 cognitively normal adults found higher amyloid or tau burden associated with faster DCTclock decline, and in the 930 participant Bio-Hermes-001 study the DCR predicted amyloid PET status. The company also reports the DCR predicting plasma p-tau217 status. That matters because disease modifying Alzheimer's therapies require confirmed amyloid pathology, so a three minute office test that predicts PET status addresses the screening failure and prescreening cost problem directly. Deployed to health systems with EHR integration and a remote administration option. Note the company's own positioning acknowledges the complementary rise of FDA cleared blood based biomarkers rather than competing with them.

The company that created the non-invasive coronary physiology category and now the broadest platform in the cardiovascular CT lane. Nasdaq listed as HTFL. The Heartflow One platform spans four functions across the CCTA pathway: RoadMap Analysis for rapid stenosis detection, FFRCT Analysis for the physiological significance of each lesion computed from a previously acquired CCTA, Plaque Analysis for quantification and staging, and Planner for intervention planning. FFRCT is the origin product and its distinguishing status is guideline recognition rather than clearance alone: it is supported by the ACC/AHA Chest Pain Guideline, which is a materially higher bar than a 510(k) and something no competitor in this lane holds. Plaque Analysis and RoadMap Analysis were cleared in October 2022, with two further clearances reported in May 2026. Critical regulatory scoping that buyers outside the US must catch: all four functions are cleared for clinical use in the United States, Bahrain, Israel, Saudi Arabia and the UAE, but only FFRCT and Planner are cleared in Europe, the United Kingdom, Australia, Canada and Japan. Plaque Analysis and RoadMap are therefore not available for clinical use in most of the developed world outside the US. The evidence base is the largest in the index for any single vendor: more than 600 peer reviewed publications, over 100 studies assessing more than 365,000 patients, and clinical use across more than 400,000 patients worldwide. Landmark studies include SCOT-HEART, the EMERALD series, the ADVANCE-DK registry with seven year follow up, SMART-CT showing a 25 percent reduction in read times, the PRECISE trial, a Mass General Brigham registry of over 15,000 patients with up to 16 years of follow up, and the DECIDE registry of roughly 22,000 patients across more than 30 US centres. Editorial note worth carrying: when the Nature Reviews Cardiology QCI Study Group benchmarked eight commercially available FDA approved plaque quantification systems head to head, the publication records that Heartflow was unable to provide the required analysis for inclusion. The largest evidence base in the category does not necessarily mean the greatest willingness to be compared directly against competitors, which is the axis on which Lunit earned credit in this index.

Oxford spinout measuring coronary inflammation rather than plaque, from the same routine coronary CT angiography scan. This is what separates it from every other vendor in the cardiovascular CT lane. Coronary inflammation inhibits lipid accumulation in adjacent fat cells, producing a measurable gradient in the perivascular adipose tissue surrounding the artery, and the CaRi-Heart FAI-Score quantifies that gradient as a Fat Attenuation Index. The clinical significance is that it detects risk in patients who look clean on conventional assessment: in the Oxford led ORFAN registry, among patients with no or minimal plaque and zero calcium at CCTA, those with the highest coronary inflammation showed roughly 9.5 to 11 times the cardiac mortality risk and around 5 times the major adverse cardiac event risk compared with those with minimal inflammation. The company operates two distinct products with different regulatory standing, and buyers must not conflate them. CaRi-Plaque, for plaque and stenosis quantification, received FDA 510(k) clearance in March 2025 and sits in the same competitive set as Cleerly, Elucid, HeartFlow and Artrya. CaRi-Heart FAI-Score, the inflammation product and the actual differentiator, is regulatory cleared in the UK, EU and Australia but remains pending FDA clearance for US clinical use, holding only a Category III CPT code approved by the AMA panel. A Category III code is an emerging technology tracking code and is not the Category I code with established payment that applies to automated plaque analysis. Evidence is unusually strong and independent: ORFAN was published in The Lancet as a multicentre longitudinal cohort externally validating the AI-Risk prognostic algorithm in an NHS population, the CRISP-CT study established incremental prognostic value of perivascular FAI beyond traditional risk factors, an ESC Congress 2025 late breaker reported FAI-Score predicting cardiac death beyond hsCRP, and a prospective trial NCT07220304 is registered. Cloud based deployment.

AI analysis of coronary and carotid CT angiography that quantifies and classifies atherosclerotic plaque morphology. PlaqueIQ received FDA 510(k) clearance in October 2024 and is distinguished by its ground truth: the convolutional neural networks were trained on carotid endarterectomy histopathology images co-registered to CTA scans, so plaque components are classified against actual tissue rather than against Hounsfield unit thresholds. Because Hounsfield values overlap between tissue types such as lipid rich necrotic core and intraplaque hemorrhage, the software interprets the spatial distribution of tissue properties across adjacent voxels instead of applying fixed HU ranges. The company markets this as CT Virtual Histology. The product reports patient, vessel, and lesion level plaque composition, with particular emphasis on lipid rich necrotic core, a plaque type associated with heart attack and stroke risk. A carotid artery version launched in October 2025, extending the same approach to stroke risk. An FFRCT product derived from the plaque algorithm, which the company argues yields concordance between plaque findings and ischemia estimates, remains pending FDA clearance and should not be treated as available. Reimbursement is established rather than theoretical: four of the seven Medicare Administrative Contractors extended coverage for AI enabled quantitative coronary plaque analysis from November 2024, the radiology benefit manager EviCore added it to coverage guidelines, and United Healthcare aligned its cardiac imaging guidelines to include coronary CTA plaque quantification across all plans from October 2025. Note that the workflow is not fully autonomous: trained analysts segment the data to create the 3D coronary model before the software classifies and quantifies tissue. Indexed alongside Cleerly, its closest comparator, with which it is routinely benchmarked in the peer reviewed literature.

Taiwan based medical imaging AI company spanning digital pathology infrastructure and diagnostic algorithms, whose aetherSlide image management platform received both FDA clearance and IVDR certification in 2026, positioning it for global expansion beyond Asia. Its algorithm portfolio includes a CE marked lymph node metastasis detector for gastric cancer that classifies and quantifies positive and negative nodes, and aetherAI Hema, described as the first bone marrow differential AI system, trained on a curated dataset of more than one million cells and reporting 15 subtype differential counts. Deployed across Chang Gung Memorial Hospital branches and developed in collaboration with National Taiwan University Hospital and Chi Mei Medical Center. Backed by Quanta Computer and Cathay Venture, and has applied to list on the Taiwan Innovation Board.

Formerly Owkin Dx, the CE-IVD marked diagnostics arm of Owkin, since spun out as an independent company named Waiv with $33M in financing. This record keeps its original address for continuity. It remains indexed separately from Owkin itself under the index rule of indexing by AI product rather than by company, and Owkin holds a separate record covering its research and pharmaceutical business. Two products established the position, both category firsts in Europe. RlapsRisk BC predicts risk of distant relapse in ER positive HER2 negative early invasive breast cancer from haematoxylin and eosin stained whole slide images combined with clinical variables including age, node involvement and tumour size, described as the first CE-IVD approved digital pathology AI diagnostic predicting relapse risk. MSIntuit CRC pre-screens colorectal tumours from routine histology to rule out microsatellite stable phenotypes, reducing the volume of confirmatory MSI testing required. Both are positioned as cheaper and more accessible alternatives to molecular and gene expression testing, using slides laboratories already produce. Following the spin out the portfolio is presented under an AI native digital pathology platform named Destra. Buyers should note that certifications and compliance disclosures published by Owkin cannot be assumed to transfer to the spun out entity, and should be confirmed with Waiv directly.

Oslo based company whose Histotype Px Colorectal predicts patient outcome in stage II and III colorectal adenocarcinoma from standard H and E stained slides, stratifying patients into low, intermediate, and high risk groups to inform whether adjuvant chemotherapy should follow surgical resection. Reported as the first CE marked product using AI to predict patient outcome from image analysis. Built on research from the Institute for Cancer Genetics and Informatics at Oslo University Hospital and trained on close to 100 million image tiles. Addresses a specific overtreatment problem the company states plainly: most stage II and III patients are cured by surgery alone, so a large majority receiving adjuvant chemotherapy gain no benefit while incurring its harms.

Chinese origin imaging AI company with US operations, whose InferRead suite spans lung nodule detection and characterization on CT, chest radiography, coronary CTA, and target reconstruction, alongside an InferOperate surgical planning suite covering thorax, liver, and urology. Holds the broadest multi jurisdiction regulatory footprint of any vendor in this lane, with authorizations from the US FDA, European CE, UK UKCA, Japan PMDA, and China NMPA. Its flagship lung CT product was first FDA cleared in 2020 and received further clearance in May 2025 for enhanced features including detection of nodules as small as 4 mm and automated lung density analysis. Deployed for tuberculosis screening programmes including UN procured deployments in Eastern Europe and Central Asia.

Deep learning medical imaging analytics company, formerly Zebra Medical Vision, acquired in November 2021 for up to 200 million dollars and now operating as the AI subsidiary of Nasdaq listed medical imaging hardware company Nano-X Imaging. Its distinguishing strategy is opportunistic population health screening: mining CT scans already acquired for unrelated clinical reasons to surface undiagnosed conditions, with cleared products covering vertebral compression fractures and low bone density associated with osteoporosis via HealthOST, coronary artery calcium quantification for cardiovascular risk, plus pneumothorax and brain bleed detection. Reported ten FDA clearances across the portfolio. Sold to hospitals, HMOs, integrated delivery networks, pharmaceutical companies, and insurers.

San Francisco company whose Digital Twin Generators are generative models trained on historical control and observational data to forecast how an individual trial participant would progress under control or standard of care. That forecast becomes a prognostic score used as a covariate in the trial analysis, a method the company calls PROCOVA, which reduces variance and can lower required sample size without introducing the confounding bias that external control arms carry. Occupies a regulatory position no other vendor in this index holds: PROCOVA received a positive qualification opinion from the European Medicines Agency in September 2022 as an acceptable statistical approach for primary analysis in Phase 2 and 3 trials with continuous endpoints, and FDA CDER subsequently commented that it concurs and that the method does not deviate from current guidance.

Paris based pathology AI company whose Cleo tools detect and quantify cancer biomarkers in whole slide images across two specialties. Cleo Breast is CE-IVDR marked as a primary diagnostic solution covering breast tissue biomarkers including mitosis counting and lymph node metastasis detection, while Cleo Skin is described by the company as the first AI tool for dermatopathology to receive CE-IVDR certification. Distinctive for a deliberately multi platform distribution strategy, with Cleo integrated into PathAI, Proscia, PathPresenter, and Gestalt environments rather than requiring its own workspace, and for running a dermatopathology clinical validation study measuring pathologist performance with and without the tool.

Stockholm based company whose Stratipath Breast is described in peer reviewed literature as the first CE-IVD marked AI image analysis tool for primary breast cancer risk stratification available for routine clinical use. Rather than detecting or quantifying a biomarker, it stratifies patients into low and high risk groups from routine hematoxylin and eosin stained slides already produced in standard care, positioning it as a prognostic alternative to molecular multigene assays that carry longer lead times and higher cost. Validated retrospectively across 2,719 primary breast cancer patients from two Swedish hospitals, and since 2025 also distributed through PathAI's AISight platform.

Palo Alto precision oncology company whose Vesta platform predicts treatment response and prognosticates outcomes from routine hematoxylin and eosin stained slides, built on a Computational Histology AI foundation trained on more than 500,000 pathologist annotations of tumors and their microenvironment. Reaches the clinic through a different regulatory route than most pathology AI indexed here: tests are offered as laboratory developed tests from the company's own CLIA certified and CAP accredited laboratory rather than as cleared devices, spanning bladder, prostate, and pancreatic cancer. Vesta Bladder Risk Stratify Dx received FDA Breakthrough Device Designation in May 2026, reported as the first AI powered digital pathology prognostic test in bladder cancer to do so.

Hamburg based computational pathology company focused on biomarker quantification from H and E, immunohistochemistry, and multiplex immunofluorescence tissue images. Holds a reported eleven CE-IVD marked algorithms spanning breast cancer markers HER2, ER, PR, and Ki-67 plus lung PD-L1, with research use only assays for prostate and other tumor types. Its BreastIHC product was described at launch as the first deep learning solution certified to distinguish tumorous from non tumorous structures at cellular level for primary diagnosis. Since 2025 the portfolio is also distributed through PathAI's AISight platform, which is separately indexed here, so a buyer may encounter these algorithms either directly or embedded in another vendor's workspace.

Danish precision pathology software company whose diagnostic products are packaged as APPs, self contained algorithms for specific biomarker scoring tasks, covering HER2, Ki67, PD-L1, lymph node metastasis detection, and invasive tumor detection across breast, lung, prostate, and colorectal cancer. Distinguished by regulatory volume under Europe's IVDR, with the PD-L1 application described as its ninth IVDR clearance, and by a commercial alliance with Agilent under which the APPs are validated for Agilent assays and the Omnis platform and sold as the Visiopharm Diagnostic Package. The APP model reflects a structural reality of pathology AI: clearances are narrow, tied to a specific tumor type, biomarker, antibody clone, and assay vendor, so breadth is achieved by accumulating many separately certified algorithms rather than one general model.

New Mexico based digital pathology company whose HALO AP Dx is an enterprise platform FDA cleared for primary diagnosis of surgical pathology slides, with clearances tied to specific scanner hardware: K232833 with the Hamamatsu NanoZoomer S360MD and K252762 adding the Leica Biosystems Aperio GT 450 DX. Operates as both a diagnostic workspace and an algorithm host, with third party AI available through an associated store, positioning it alongside Proscia and PathAI as platform infrastructure rather than a single algorithm vendor. The company maintains a deliberate two product split in the United States: HALO AP Dx for clinical primary diagnosis, and HALO AP as research use only, explicitly not FDA cleared for diagnostic use.

Cardiovascular imaging company applying AI to coronary CT angiography to quantify and characterize atherosclerotic plaque, producing comprehensive phenotyping of coronary artery disease from non invasive imaging. Distinguished in this index by reimbursement achievement rather than clearance alone: its technology underpins Category I CPT codes, multiple Medicare Administrative Contractor coverage determinations, and commercial payer policies reported to span more than 86 million covered lives. Evidence base includes the multicenter international CONFIRM2 registry.

Biomedical AI company building generative and agentic tools for pathology, whose PathChat co-pilot combines pathology foundation models pretrained on histology image and image text datasets with a custom trained multimodal large language model, enabling conversational analysis of high resolution slides and clinical data. The copilot is presented as usable from a microscope, a slide viewer or a smartphone, which removes the usual prerequisite of a completed digital pathology programme. A second product, Judith, is an agent for automating AI model development for biomedical image analysis. Extends research published in Nature from an academic lab at a major Boston hospital system; the company's whole slide foundation model TITAN is described in the literature as pretrained on 335,645 whole slide images and fine tuned partly on synthetic captions generated by PathChat itself. Received FDA Breakthrough Device Designation for its diagnostic version, which the company states plainly does not imply clearance or approval. In January 2026 the company announced its acquisition by AstraZeneca to advance AI driven oncology research and development at global scale; this record grades the products rather than the parent, and the ownership relationship is treated on the governance axis. Earlier research collaborations were announced with Techcyte, also indexed here, and with illumiSonics.

Publicly traded Finnish deep learning pathology company offering cloud based image analysis across both clinical diagnostics and preclinical research. Holds IVDR certification and describes itself as Europe's leading provider of CE-IVD marked digital pathology AI, with clinical suites spanning breast, lung, prostate, colorectal, and gastric cancer plus lymph node metastasis detection. Recent models are built on a foundation engine designed to perform across real world variation in sample quality, staining, and scanning.

Digital pathology company whose AISight image management system holds FDA 510(k) clearance for primary diagnosis, paired with a large portfolio of AIM interpretation modules covering commercially significant oncology biomarkers. Its AIM-MASH tool became the first AI powered pathology Drug Development Tool to receive FDA and EMA qualification, allowing pharmaceutical sponsors to use it for endpoint assessment in registrational trials. Sold its diagnostics laboratory business to a national reference lab in 2024 while licensing the platform back, and entered a definitive merger agreement with Roche in May 2026.

Cancer diagnostics company describing itself as the first and most widely deployed AI platform in pathology, with prostate, breast, and gastric solutions used in routine clinical practice worldwide. Its prostate product received FDA 510(k) clearance as an in vitro diagnostic that generates heatmaps flagging small and rare cancers missed on initial assessment, functioning as a second read safety net rather than a primary reader. Notable in this index for holding an unusually complete set of published security and quality certifications.

Computational pathology company that produced the first FDA authorized AI based digital pathology product, Paige Prostate, cleared via the De Novo pathway for cancer detection support. Subsequently pursued foundation model scale work in oncology imaging and received FDA Breakthrough Device designation for a pan cancer detection tool spanning common and rare variants across multiple tissue types. Acquired by Tempus in August 2025 for a reported 81.25 million dollars, making it now part of an indexed vendor rather than an independent competitor.

Cancer focused imaging AI company, publicly listed in Korea, whose INSIGHT suite covers chest X-ray, mammography, and digital breast tomosynthesis. Distinguished less by product breadth than by evidence depth: more than 100 peer reviewed publications spanning The Lancet Digital Health, JAMA Oncology, and Radiology, including third party head to head validations against competing commercial products. Lunit completed its acquisition of Volpara Health Technologies in May 2024. Volpara, founded in 2009 and based in Wellington, New Zealand, made breast screening software covering breast density assessment, imaging quality management and personalised screening, and brought an installed base reported at more than 2,000 United States medical sites. The Volpara name was retired in November 2025, when the business was folded into the Lunit brand and renamed Lunit International, taking commercial operations across the United States, Oceania, Europe and Asia while the Seoul headquarters retained research and new product development. A buyer searching for Volpara or Volpara Health is searching for this vendor. Reported reach after the integration is more than 10,000 healthcare providers across more than 65 countries, with distribution partly through imaging hardware OEM relationships.

Global radiology AI company with the broadest chest X-ray regulatory footprint in the market, spanning nine products across X-ray and CT. Its qXR suite detects, localizes, and categorizes findings on plain film chest radiographs including lung nodules, pneumothorax, and pleural effusion, alongside qER neurocritical products covering intracranial hemorrhage, cranial fracture, and midline shift. Notably the only chest X-ray computer aided detection device cleared by the FDA with a Predetermined Change Control Plan, allowing model updates without a new submission.

Digital pathology software company whose Concentriq platform manages and analyzes whole slide pathology data for clinical laboratories and life sciences organizations. Its diagnostic edition is FDA 510(k) cleared and CE-IVDR marked for primary diagnosis, while the research edition remains labeled Research Use Only, a distinction the company draws explicitly. Embedded AI recommends stain panels and ancillary tests from tissue appearance and scores image analysis biomarkers including PD-L1, HER2, and Ki-67 in the viewer.

Ophthalmology company combining patented imaging hardware with machine learning and generative AI to standardize dry eye disease diagnosis, consolidating what are conventionally ten separate gold standard tests into a single exam of a few minutes and returning condition detection with personalized treatment recommendations for clinician approval. Montreal based and pre commercial, with a Quebec health agency subdivision assessing image quality and the accuracy of its diagnostic and treatment recommendation algorithms.

Point of care EEG company combining a rapidly deployable headband with the Clarity machine learning algorithm, which interprets EEG every ten seconds across all channels to produce a seizure burden estimate and alert bedside clinicians to suspected status epilepticus. Designed for emergency departments and intensive care units where conventional EEG and neurology interpretation are not immediately available. Publicly traded, and the only AI point of care EEG cleared across the full age range from preterm neonates through adults.

ECG led diagnostics software company whose AccurECG Analysis System is an FDA cleared Class II Software as a Medical Device for fully automated, near real time ECG interpretation. The platform is device agnostic, ingesting data from patches, Holter monitors, and telemetry devices, and performs beat by beat analysis, ectopic beat detection, heart rate measurement, and automated interpretation of thirteen rhythm classifications. A pipeline of ECG derived biomarkers is in development under FDA Breakthrough Device Designation.

Clinical stage biotechnology company applying machine learning to human tissue derived multi omic data through its CONVERGE platform, which the company describes as an all in human closed loop system that pairs one of the field's larger proprietary patient tissue databases with computational target prediction, validated in its own wet laboratories. Known for taking an AI discovered ALS candidate into human trials; following a Phase 1 efficacy miss the company refocused on the discovery platform and pharmaceutical partnerships.

Respiratory diagnostics company developing Sylvee, a chest worn wearable that uses patented active acoustic resonance, projecting low frequency sound into the lungs and analyzing the returning signal with machine learning, to measure lung structure and function. Positioned to replace effort dependent spirometry with a passive test and to enable continuous home monitoring for COPD and small airway disease. Backed in part by NIH small business funding; the device is investigational and not FDA cleared.

Precision oncology clinical decision support company, spun out of Hungarian medical technology firm Oncompass Medicine, with offices in Cambridge and Budapest. Its Digital Drug Assignment platform analyzes a patient's tumor associated genetic alterations against research derived evidence and returns a ranked list of targeted therapies most likely to be effective, scoring each drug and genomic profile match. Positioned to support molecular tumor board recommendations rather than replace them.

Imaging AI company focused on prostate cancer and theranostics, built around PSMA PET/CT. Three products cover the pathway: DeepPSMA for automated lesion detection and whole body tumor burden quantification, SelectPSMA for predicting which patients will respond to PSMA targeted radioligand therapy, and TrackPSMA for automated longitudinal treatment response evaluation. Products are positioned for clinical and research decision support and are not FDA cleared.

Precision oncology company operating hospital linked genomics laboratories across India, Dubai, Nepal, and the Philippines, paired with OncoTwin, an AI clinical decision support platform that draws treatment insights from real world clinico genomic and outcomes linked data. Its stated thesis is that most genomic reference data represents Caucasian populations, and it builds population specific panels for South Asian and other underrepresented groups.

Note on naming: this is Artera of Los Altos, California (artera.ai), developer of multimodal AI cancer tests. It is unrelated to the separately indexed Artera of Santa Barbara (artera.io), which makes patient communication agents. The two companies share a name and nothing else. The ArteraAI Prostate Test is a multimodal artificial intelligence model combining digitized histopathology images from an existing biopsy with structured clinical data including age, PSA, and tumor stage, producing a continuous risk score from 0 to 1 with pre established cut points corresponding to roughly 3 percent and 10 percent estimated ten year risk of distant metastasis. It requires no additional procedure because it reads tissue already taken. Beyond prognosis it is predictive: for NCCN intermediate risk patients it estimates whether adding short term androgen deprivation therapy to radiation will reduce risk, which the literature describes as the first predictive biomarker for that decision. The algorithm is pre established and locked at version 1.2, developed from large datasets and multiple phase 3 randomized trials with up to 15 years of follow up. Regulatory and guideline standing is unusually complete: FDA De Novo marketing authorization in August 2025, inclusion in the NCCN Clinical Practice Guidelines for Prostate Cancer as the first and only AI risk stratification tool, and CMS coverage with a payment rate effective January 2024. In June 2026 the company introduced a digital pathology based test providing individual risk estimates in metastatic hormone sensitive prostate cancer. Co-founded by Felix Y. Feng of UCSF; CEO Andre Esteva.

AI digital pathology platform spanning human, veterinary, and environmental laboratories, developing in this field since 2013. Techcyte Fusion is positioned as the first digital workflow integrating anatomic and clinical pathology in one platform, with deep learning models identifying parasitic cells, bacteria, and cancer cells, plus digitization enabling remote case review. Product areas include parasitology, bacteriology, hematology with a peripheral blood smear classifier, cervical cytology, and bladder cancer surveillance. Regulatory status is the decisive buyer fact and the company states it plainly: the anatomic and clinical pathology platform and its human products are Research Use Only in the United States, while Fusion carries CE-IVDD marking in Europe. The architecture is deliberately open rather than proprietary, connecting to numerous slide scanners, laboratory information systems, and third party AI developers through a Fusion Partner Program; one such partner, Modella AI, brought its PathChat research copilot to the platform and was subsequently acquired by AstraZeneca in January 2026. A long running Mayo Clinic collaboration provides access to the Safe Harbour dataset of more than 17 million de-identified slides and pathology reports for model development. The company reports its veterinary segment is already profitable, with human and environmental segments targeted for profitability by 2027, and raised $15 million to expand the platform. Headquartered in Orem, Utah; CEO Ben Cahoon.

Indexed for what is commercially available today, which requires care because the company's own AI algorithms are not yet cleared. MyoVista Insights is a cloud based ECG reporting and management platform, in phased rollout since May 2025 and shipping at version 1.3 as of June 2026, positioned to replace on premise ECG management software. Its AI-ECG Algorithm Marketplace, introduced in version 1.3, integrates third party algorithm results into the platform, and the first algorithm made available is Bunkerhill Health's FDA cleared ECG-EF model detecting reduced left ventricular ejection fraction at or below 40 percent from a routine 12-lead ECG. Bunkerhill is separately indexed here, so this is a distribution relationship between two vendors in this index rather than a HeartSciences algorithm. The company's own pipeline is not yet available: the MyoVista wavECG device, a 12-lead resting ECG built to host AI-ECG algorithms, was submitted for 510(k) clearance in December 2025 and clearance was not confirmed at the time of this record; its impaired cardiac relaxation algorithm was deliberately separated from that submission to complete additional validation against revised American Society of Echocardiography guidelines for diastolic dysfunction; and its low ejection fraction algorithm remains in pre submission work. Underlying intellectual property is licensed in part from the Icahn School of Medicine at Mount Sinai. Assistive AI-ECG assessments are eligible for Medicare reimbursement under the Hospital Outpatient Prospective Payment System at APC 5734. NASDAQ: HSCS.

AI models of tumor and immune biology applied to precision oncology, serving both clinical care and drug development. The Tumor Portrait test integrates DNA and RNA exome sequencing into a single end to end assay, approved under CLIA, CAP, and the New York State Department of Health, producing tumor driver, microenvironment, and actionable biomarker characterization from one sample. Kassandra is the company's cell deconvolution model for reconstructing tumor microenvironment composition. Clinical and analytical validation was published in Communications Medicine, part of the Nature portfolio, across more than 2,200 tumors, reporting high reproducibility and clinical actionability in 98 percent of cases. Research collaborations span MD Anderson Cancer Center, Weill Cornell Medicine, and the Parker Institute for Cancer Immunotherapy, with nine abstracts accepted at ASCO 2026, and biopharma partnerships include Takeda for trial design and biomarker signature identification. A Japan joint venture operates with NEC Corporation and Japan Industrial Partners.

Rare disease genomic diagnosis (NASDAQ: WGS), applying AI and expert variant interpretation to exome and genome sequencing. GeneDx Infinity is the company's rare disease genomic dataset, accumulated over roughly 25 years and described by the company as the largest and most comprehensive of its kind. Products span ExomeDx and GenomeDx, both granted FDA Breakthrough Device designation, ultraRapid genome sequencing returning results for NICU and PICU patients in as little as 48 hours, and GenomeDx Prenatal, a phenotype informed trio based whole genome test for pregnancies with fetal anomalies. The company is the sole commercial testing provider for the NIH BEACONS genomic newborn screening initiative, which aims to enroll up to 30,000 newborns across as many as ten states. Reimbursement position is unusually well documented: Medicaid coverage for exome or genome sequencing in the pediatric outpatient setting across 38 states and for rapid genome sequencing in the NICU across 17. Full year 2025 revenue of $427.5 million with 2026 guidance of $475 to $490 million.

Precision oncology company (NASDAQ: CAI) combining comprehensive molecular profiling with AI interpretation. MI Cancer Seek received FDA approval in November 2024 and is, per the company, the first and only assay performing simultaneous whole exome and whole transcriptome sequencing with FDA approved companion diagnostic indications for solid tumors, analyzing more than 23,000 genes from a single tissue sample for adult and pediatric patients. The CodeAI platform runs over a large multimodal clinico genomic dataset to generate Caris AI Insights, a set of proprietary signatures predicting therapy response, tissue of origin, and metastasis risk, delivered in the Caris Molecular Tumor Board Report. Signatures added through 2026 include brain metastasis risk in breast and lung cancer, trained on 12,994 NSCLC and 3,371 breast cancer cases with matched survival outcomes. MI Clarity applies AI and computational pathology to stratify breast cancer recurrence risk without genomic sequencing. Caris Assure is the blood based platform. Went public in June 2025 raising $494 million; biopharma partners include a large alliance with Merck KGaA.

Enterprise genomics platform for health systems, payers, and life sciences. Health systems run population genomics programs on Helix infrastructure, covering recruitment, clinically actionable disease screening, return of results, and research, built on the proprietary Exome+ assay and a CLIA certified, CAP accredited sequencing lab. The Helix Research Network spans roughly 20 health system members and a reported 400,000+ sequenced participants, feeding GenoSphere, a linked clinico-genomic dataset that passed 500,000 records in June 2026, each combining Exome+ sequencing with an average of 13 years of EHR history and 8 years of claims. AI tooling is a recent layer rather than the foundation: an AI Cohort Builder launched June 2026 and a Model Context Protocol connector for querying the dataset launched July 2026. Health system programs include Cone Health, Sanford Health, WellSpan, St. Luke's University Health Network, HealthPartners, Nebraska Medicine, and Memorial Hermann.

Blood based early cancer detection built on a multiomics platform that analyzes genomic, epigenomic, and proteomic biomarkers and applies machine learning classifiers to detect cancer signals in circulating tumor DNA at single base methylation resolution. SimpleScreen CRC, the colorectal screening test, has a Premarket Approval application under FDA review submitted August 2025, with the company stating an expected decision in mid 2026. It is not FDA approved, and is currently offered at select pilot sites as a laboratory developed test. The pivotal PREEMPT CRC validation study enrolled 48,995 average risk adults across more than 200 sites and was published in JAMA in 2025, and blood based testing was included in the American Cancer Society's updated colorectal screening guideline in 2026. Reported sensitivity differs by assay version and by venue: the published first generation results give roughly 81 percent for colorectal cancer and 14 percent for advanced precancerous lesions, company materials describe an updated version at 85 percent and 22 percent, and a July 2026 securities filing reports 80.4 percent and 18.2 percent. Establish which analysis a figure comes from before using it. Under an exclusive license signed with Exact Sciences in August 2025, SimpleScreen CRC will be commercialized by Abbott, which acquired Exact Sciences in March 2026, so the buyer's counterparty on approval is Abbott rather than Freenome. Freenome retains a narrower product of its own, SimpleScreen CRC paired with its SimpleScreen Lung laboratory developed test, offered solely to patients eligible for both screenings. The company completed its merger with Perceptive Capital Solutions Corp on 20 July 2026 and trades on Nasdaq as FRNM.

Lung cancer diagnostics company (NASDAQ: BIAF). CyPath Lung is a noninvasive test for early stage lung cancer that combines flow cytometry of a patient sputum sample with automated analysis developed by machine learning, using a fluorescent porphyrin preferentially taken up by cancer and cancer related cells. Per the company's SEC filings, AI standardizes sample data analysis and patient test results. Physicians order the test to assess patients with small indeterminate pulmonary nodules. In a clinical trial of high risk patients with nodules under 20 millimeters, the company reports 92 percent sensitivity, 87 percent specificity, 88 percent accuracy, and 99 percent negative predictive value. Marketed as a laboratory developed test through the company's own CLIA laboratory and explicitly not intended as a sole diagnostic tool.

Multi cancer early detection company (NASDAQ: GRAL). The Galleri test uses targeted methylation sequencing with machine learning to detect a cancer signal from a blood draw and predict the tissue of origin. Reported to detect signals across more than 50 cancer types. The evidence base is unusually deep for this index: PATHFINDER 2 enrolled 25,490 participants and the NHS-Galleri trial enrolled more than 140,000 asymptomatic participants in England, the only prospective randomized controlled trial of a multi cancer early detection test for population screening. GRAIL submitted the final module of its FDA Premarket Approval application for Galleri in January 2026; the test carries FDA Breakthrough Device designation (2018) and is currently offered as a laboratory developed test.

Cloud native genomics analysis company (NASDAQ: SOPH). The SOPHiA DDM platform applies machine learning with patented algorithms to call, annotate, and pre classify variants from next generation sequencing data, technology agnostic across sequencing instruments, with genomics, radiomics, and multimodal analytics modules. Deployed as software that hospitals and labs run themselves: at Mount Sinai, for example, SOPHiA provides the analytical software while the health system runs it as a laboratory developed test in its own CLIA certified, CAP accredited lab. The platform reports a network of more than 750 hospitals, academic centers, and labs and a federated learning model across participating institutions. Certain applications are research use only and regional clearance varies.

Precision medicine company (NASDAQ: TEM) whose provider software is what this index covers: Next, an AI clinical decision support system that alerts clinicians to patients who may have fallen off care guidelines, backed by a vendor reported 662 patient prospective study across six sites; Hub, a physician platform rebuilt on an agentic architecture including a prior authorization agent; and David, a generative AI clinical assistant deployed directly into the EHR, with Northwestern Medicine as the first health system. Tempus acquired Deep 6 AI in March 2025, adding a precision research platform that applies natural language processing to structured and unstructured EMR data to match patients to clinical trials in near real time and to generate real world evidence. Deep 6 reports real time EMR feeds across more than 30 health systems, an ecosystem of over 1,000 research facilities including 18 academic medical centers and 11 NCI designated cancer centers, and that sites find more than 25 percent more patients than with traditional recruitment; the company notes 92 percent of trial inclusion and exclusion criteria benefit from unstructured data and that 15 to 20 percent of eligible patients are found through unstructured data alone. Outputs are positioned as decision support requiring trial team validation before action. The sequencing and pharma services businesses are context, not indexed products.