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    <title>AI Health Index: healthcare AI change log</title>
    <link>https://aihealthindex.io/changelog</link>
    <atom:link href="https://aihealthindex.io/feeds/changes.xml" rel="self" type="application/rss+xml" />
    <description>Material product changes at healthcare AI vendors, tracked by AI Health Index. Every entry is dated and cited to a public source.</description>
    <language>en-us</language>
    <copyright>Free to reuse with a visible link to aihealthindex.io. Terms: https://aihealthindex.io/use-this-data</copyright>
    <lastBuildDate>Fri, 25 Sep 2026 12:00:00 GMT</lastBuildDate>
    <ttl>720</ttl>
    <image>
      <url>https://aihealthindex.io/icon-192.png</url>
      <title>AI Health Index: healthcare AI change log</title>
      <link>https://aihealthindex.io/changelog</link>
    </image>
    <item>
      <title>The 25 Sep Artera Harmony Federal Edition release changes Intake Hub to match patient forms to appointments using the EHR's event ID, so…</title>
      <link>https://aihealthindex.io/changelog/artera</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab90c10ee3c2977980e6546</guid>
      <pubDate>Fri, 25 Sep 2026 12:00:00 GMT</pubDate>
      <category>EHR / interoperability</category>
      <category>Patient Voice Agents</category>
      <category>Healthcare Administrative Automation</category>
      <description><![CDATA[<p>The 25 Sep Artera Harmony Federal Edition release changes Intake Hub to match patient forms to appointments using the EHR's event ID, so renaming an appointment type in the EHR no longer stops forms from being assigned. Details from a patient's uploaded ID or insurance card now fill in the rest of an Intake Hub form automatically, and the notes say groundwork is in place to write form answers back to the EHR.</p><p><strong>Why it matters:</strong> Matching on the EHR event ID removes a silent failure where intake forms stopped going out after an EHR configuration change. Card based auto fill cuts manual entry for patients before the visit. EHR write back is not yet live.</p><p>Impact: Low. Verification: Verified. Type: EHR / interoperability.</p><p>Evidence: <a href="https://knowledge.artera.io/en_US/release-notes-artera-harmony-federal-edition/2026-releases-artera-harmony-federal-edition">Vendor documentation</a></p><p>Source: <a href="https://aihealthindex.io/changelog/artera">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
    </item>
    <item>
      <title>Artera AI agents can now listen for the voicemail beep and start speaking when recording begins, turned on for each agent individually.</title>
      <link>https://aihealthindex.io/changelog/artera</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab90c10ee3c2977980e6545</guid>
      <pubDate>Fri, 25 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Patient Voice Agents</category>
      <category>Healthcare Administrative Automation</category>
      <description><![CDATA[<p>Artera AI agents can now listen for the voicemail beep and start speaking when recording begins, turned on for each agent individually. The same release moves website syncing into an AI agent knowledge base to a background process so it no longer slows live patient conversations, and adds automated tests that check an agent's responses before changes go live.</p><p><strong>Why it matters:</strong> Outbound voice agents that talk over a voicemail greeting leave clipped, unusable messages, so beep detection makes reminder and recall calls land when patients do not answer. Pre release response testing is a governance control buyers can ask to see.</p><p>Impact: Medium. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://knowledge.artera.io/en_US/release-notes-artera-harmony-federal-edition/2026-releases-artera-harmony-federal-edition">Vendor documentation</a></p><p>Source: <a href="https://aihealthindex.io/changelog/artera">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
    </item>
    <item>
      <title>Spring Health added a Harm From Others rubric to VERA-MH, its open source benchmark for mental health AI safety, and opened it for 60 days…</title>
      <link>https://aihealthindex.io/changelog/spring-health</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab85e9bd92e5616ac6dc818</guid>
      <pubDate>Fri, 25 Sep 2026 12:00:00 GMT</pubDate>
      <category>Safety / governance</category>
      <category>Behavioral Health AI</category>
      <description><![CDATA[<p>Spring Health added a Harm From Others rubric to VERA-MH, its open source benchmark for mental health AI safety, and opened it for 60 days of public comment. The rubric evaluates how an AI system responds when an adult describes risk of physical or sexual violence from another person, scored across five areas using 100 personas, and is published in the VERA-MH repository.</p><p><strong>Why it matters:</strong> Open safety criteria give buyers a common yardstick for mental health AI, including tools from other vendors. Buyers can use the draft rubric now to ask any vendor how its AI detects and escalates these situations.</p><p>Impact: Medium. Verification: Verified. Type: Safety / governance.</p><p>Evidence: <a href="https://www.springhealth.com/news/spring-health-opens-vera-mh-harm-from-others-safety-rubric-for-public-comment">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/spring-health">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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    <item>
      <title>InsightRX released Gemini 2026.2, an update to the model selection engine in InsightRX Nova that adds a new general adult vancomycin…</title>
      <link>https://aihealthindex.io/changelog/insightrx</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab90c10ee3c2977980e6544</guid>
      <pubDate>Thu, 24 Sep 2026 12:00:00 GMT</pubDate>
      <category>Model / architecture</category>
      <category>Medication Safety &amp; Prescribing</category>
      <category>Clinical Decision Support</category>
      <description><![CDATA[<p>InsightRX released Gemini 2026.2, an update to the model selection engine in InsightRX Nova that adds a new general adult vancomycin model, McCarthy 2026, plus CKD-EPI eGFR versions of the published models that improved with that input. McCarthy 2026 was fit on a stratified sample drawn from 549,171 patients across 304 US organizations, scales body size on fat free mass and bends the eGFR effect on clearance at 90 mL/min/1.73 m2. InsightRX reports that the release raised individual prediction accuracy from 66% to 68%, cut bias (MPE) from 1.8% to 0.9% and cut error (NRMSE) from 28% to 27% versus Gemini 2026.1.</p><p><strong>Why it matters:</strong> Health systems using Gemini get the new model recommendations automatically, and InsightRX states the Hughes 2024 obesity model is now mostly selected only for patients with obesity. It also shows the vendor retraining and revalidating models on network data after deployment. The accuracy gains are vendor reported and modest.</p><p>Impact: Medium. Verification: Verified. Type: Model / architecture.</p><p>Evidence: <a href="https://blog.insight-rx.com/resources/continuous-learning-in-practice-three-ways-to-improve-adult-vancomycin-models">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/insightrx">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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    <item>
      <title>Helix launched Helix Research Workspaces, a Trusted Research Environment inside Helix Explorer built on the Databricks Data + AI platform…</title>
      <link>https://aihealthindex.io/changelog/helix</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab90c10ee3c2977980e6543</guid>
      <pubDate>Thu, 24 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Diagnostics &amp; Genomics</category>
      <description><![CDATA[<p>Helix launched Helix Research Workspaces, a Trusted Research Environment inside Helix Explorer built on the Databricks Data + AI platform, giving approved partners governed compute, storage and analysis tools over more than 550,000 GenoSphere clinicogenomic records (Exome+ data linked to 13+ years of EHR history plus claims). It ships a genomic analysis toolkit for GWAS style, PheWAS and gene burden studies, an AI coding assistant Helix describes as trained on GenoSphere, no code data browsing, project notebooks with built in data access controls and monitoring, and real time job status and compute cost tracking.</p><p><strong>Why it matters:</strong> Pharma and health system research teams can run population scale genomic analysis inside a Helix provisioned, access controlled workspace instead of standing up their own infrastructure, which changes the deployment and data governance model for GenoSphere licensees beyond the earlier Cohort Builder.</p><p>Impact: Medium. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://www.helix.com/press-releases/helix-partners-with-databricks-to-launch-tre-for-population-scale-clinicogenomic-research">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/helix">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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    <item>
      <title>Edison Scientific: Kosmos can now read licensed full text research from specialist journals across Springer Nature's Nature portfolio when it generates…</title>
      <link>https://aihealthindex.io/changelog/edison-scientific</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab90c10ee3c2977980e6542</guid>
      <pubDate>Thu, 24 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Drug Discovery AI</category>
      <category>Clinical Trials AI</category>
      <description><![CDATA[<p>Kosmos can now read licensed full text research from specialist journals across Springer Nature's Nature portfolio when it generates hypotheses or evaluates targets, under a subscription agreement Edison announced on 24 September. Kosmos links each surfaced article to its Version of Record, so outputs reflect corrected versions including retractions and editors' notes. Edison states the Nature portfolio is accessible in Kosmos as of the announcement date and calls it the first of several content partnerships.</p><p><strong>Why it matters:</strong> R&amp;D teams evaluating an AI scientist need to know which licensed literature grounds its conclusions, and retraction aware Version of Record linking reduces the risk of hypotheses built on withdrawn findings.</p><p>Impact: Medium. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://edisonscientific.com/news/bringing-trusted-research-into-kosmos-our-agreement-with-springer-nature">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/edison-scientific">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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    <item>
      <title>Veeva Systems: Veeva announced Study Builder Agent, which configures Veeva EDC forms, visits and edit checks and Veeva DQS listings directly from a study…</title>
      <link>https://aihealthindex.io/changelog/veeva-systems</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab85e9bd92e5616ac6dc817</guid>
      <pubDate>Thu, 24 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Clinical Trials AI</category>
      <description><![CDATA[<p>Veeva announced Study Builder Agent, which configures Veeva EDC forms, visits and edit checks and Veeva DQS listings directly from a study protocol, reusing an organization's existing standards and the CDISC USDM model, and generates test data. Veeva says it can bring study configuration down to as little as one day. It is planned for early adopter availability in December 2026, is included in EDC with no additional license, and is delivered as a Claude Cowork plugin.</p><p><strong>Why it matters:</strong> Study build is one of the slowest steps in trial startup, so the one day claim is worth testing on a real protocol once early adopter access opens. Sponsors should ask which study designs the agent handles and what a person still reviews before a build goes live.</p><p>Impact: Medium. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://ir.veeva.com/news/news-details/2026/New-Veeva-Study-Builder-Agent-to-Configure-Clinical-Studies-in-as-Little-as-One-Day/default.aspx">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/veeva-systems">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Insilico Medicine: Insilico announced that Model Context Protocol servers are now available across its Pharma.AI software, so outside AI agents can connect…</title>
      <link>https://aihealthindex.io/changelog/insilico-medicine</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab85e9bd92e5616ac6dc816</guid>
      <pubDate>Thu, 24 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Drug Discovery AI</category>
      <category>Clinical Trials AI</category>
      <description><![CDATA[<p>Insilico announced that Model Context Protocol servers are now available across its Pharma.AI software, so outside AI agents can connect directly to its biology, chemistry and biologics engines, including Generative Biologics, PandaOmics and Chemistry42, and run multistep discovery workflows. The announcement previews a 30 September webinar that will present new PandaOmics Agent skills and other platform updates.</p><p><strong>Why it matters:</strong> MCP access lets a customer's own agents drive Insilico's engines, which turns Pharma.AI from a set of applications into a component of the customer's stack. Teams should ask how data sent through those servers is logged and whether it is used to train Insilico's models.</p><p>Impact: Medium. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://insilico.com/news/pr84b6b87c28897f2c680e-pharma-ai-2026-fall-update-preview-agentic-ai-takes-the-wheel-of-pharmaceutical-intelligence">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/insilico-medicine">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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    <item>
      <title>Corti's Guided Generation now passes user edited, user added and discarded facts to the model with explicit type metadata.</title>
      <link>https://aihealthindex.io/changelog/corti</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab85e9bd92e5616ac6dc815</guid>
      <pubDate>Thu, 24 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Ambient Scribes</category>
      <description><![CDATA[<p>Corti's Guided Generation now passes user edited, user added and discarded facts to the model with explicit type metadata. Edited facts take precedence over the transcript where the two conflict, and discarded facts are excluded from the note even when the transcript mentions them. Previously, edits and discards were not reliably reflected in the generated note.</p><p><strong>Why it matters:</strong> This closes a common gap in ambient documentation, where a clinician's correction is undone by the next draft. Developers building on Corti should retest note generation, since conflicts now resolve in the clinician's favor rather than the audio's.</p><p>Impact: Medium. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://docs.corti.ai/release-notes/textgen">Vendor documentation</a></p><p>Source: <a href="https://aihealthindex.io/changelog/corti">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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    <item>
      <title>The FDA Molecular and Clinical Genetics Devices Panel voted on GRAIL's Premarket Approval application for the Galleri multi cancer early…</title>
      <link>https://aihealthindex.io/changelog/grail</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab90c10ee3c2977980e6541</guid>
      <pubDate>Wed, 23 Sep 2026 12:00:00 GMT</pubDate>
      <category>Regulatory / FDA</category>
      <category>Diagnostics &amp; Genomics</category>
      <description><![CDATA[<p>The FDA Molecular and Clinical Genetics Devices Panel voted on GRAIL's Premarket Approval application for the Galleri multi cancer early detection blood test, for screening adults aged 50 and older. The 10 voting members were unanimous on safety, voted 6 to 4 on effectiveness, and voted 7 to 2 with one abstention that benefits outweigh risks. FDA is not bound by the vote and GRAIL expects a final PMA decision in the coming months.</p><p><strong>Why it matters:</strong> Galleri is the first multi cancer early detection test to reach a PMA panel, and approval would change its regulatory standing for payers and health systems weighing coverage and adoption. The split 6 to 4 effectiveness vote is the risk to watch before FDA decides.</p><p>Impact: High. Verification: Verified. Type: Regulatory / FDA.</p><p>Evidence: <a href="https://grail.com/press-releases/fda-advisory-committee-votes-in-favor-of-approval-of-grails-galleri-multi-cancer-early-detection-test/">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/grail">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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    <item>
      <title>Aidoc received FDA Breakthrough Device Designation for CARE Chest X-Ray Triage, built on its CARE foundation model, covering triage of…</title>
      <link>https://aihealthindex.io/changelog/aidoc</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab85e9bd92e5616ac6dc814</guid>
      <pubDate>Wed, 23 Sep 2026 12:00:00 GMT</pubDate>
      <category>Regulatory / FDA</category>
      <category>Radiology &amp; Imaging AI</category>
      <category>Clinical Decision Support</category>
      <category>Health System AI Platforms</category>
      <description><![CDATA[<p>Aidoc received FDA Breakthrough Device Designation for CARE Chest X-Ray Triage, built on its CARE foundation model, covering triage of pneumomediastinum and lobar or lung collapse. It is Aidoc's third breakthrough designation in just over a year, after CARE Multi-Triage Body CT and CARE First Read for Chest X-Ray. The 510(k) is under FDA review and the product is not yet available for sale in the United States.</p><p><strong>Why it matters:</strong> A breakthrough designation can speed FDA review but does not clear the product. Radiology groups interested in foundation model triage for chest films should treat this as a roadmap signal and ask Aidoc for expected clearance timing.</p><p>Impact: Medium. Verification: Verified. Type: Regulatory / FDA.</p><p>Evidence: <a href="https://www.aidoc.com/learn/blog/fda-breakthrough-device-designation-for-care-chest-x-ray-triage/">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/aidoc">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Indica Labs: A Voicebrook VoiceOver PRO integration with the HALO AP platform is now available, adding voice control of case and slide navigation…</title>
      <link>https://aihealthindex.io/changelog/indica-labs</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab90c10ee3c2977980e6540</guid>
      <pubDate>Tue, 22 Sep 2026 12:00:00 GMT</pubDate>
      <category>EHR / interoperability</category>
      <category>Digital Pathology AI</category>
      <category>Diagnostics &amp; Genomics</category>
      <category>Clinical Trials AI</category>
      <description><![CDATA[<p>A Voicebrook VoiceOver PRO integration with the HALO AP platform is now available, adding voice control of case and slide navigation (zoom, pan, annotation, tab switching) and voice ordering of stains and AI analyses. A single command pulls HALO Clinical AI biomarker results such as ER and PR percentages into the matching CAP cancer protocol checklist, and sites that report inside HALO AP can pass results through to the LIS.</p><p><strong>Why it matters:</strong> Labs running HALO Clinical AI no longer need a pathologist to re key biomarker values into the synoptic report, which removes a transcription error point in a clinically weighted field. HALO Clinical AI remains Research Use Only in the US, so automated result capture applies to clinical reporting only where the product is cleared or marked.</p><p>Impact: Medium. Verification: Verified. Type: EHR / interoperability.</p><p>Evidence: <a href="https://indicalab.com/news/press-release/voicebrook-announces-digital-pathology-integration-with-indica-labs-delivering-automated-ai-biomarker-reporting-and-hands-free-navigation/">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/indica-labs">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>GRAIL: Nature Medicine published PATHFINDER 2, the registrational US study of Galleri, with 35,878 enrolled and 32,007 participants analyzable…</title>
      <link>https://aihealthindex.io/changelog/grail</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab90c10ee3c2977980e653f</guid>
      <pubDate>Tue, 22 Sep 2026 12:00:00 GMT</pubDate>
      <category>Clinical evidence</category>
      <category>Diagnostics &amp; Genomics</category>
      <description><![CDATA[<p>Nature Medicine published PATHFINDER 2, the registrational US study of Galleri, with 35,878 enrolled and 32,007 participants analyzable for performance. The test showed a 0.54% cancer detection rate, 60.3% positive predictive value, 99.64% specificity, 39.3% episode sensitivity for all cancers (69.8% for a 12 cancer subgroup) and 91.3% cancer signal origin accuracy. Of 35,335 safety analyzable participants, 0.6% had invasive procedures and no serious study related adverse events were reported.</p><p><strong>Why it matters:</strong> These are the peer reviewed performance and safety figures behind the PMA, giving buyers a published US intended use benchmark for follow up workload and false positive burden. Results were first presented at ASCO in May 2026, so the change is the peer reviewed publication.</p><p>Impact: Medium. Verification: Verified. Type: Clinical evidence.</p><p>Evidence: <a href="https://www.nature.com/articles/s41591-026-04618-w">Peer-reviewed publication</a></p><p>Source: <a href="https://aihealthindex.io/changelog/grail">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>GRAIL: Nature Medicine published Galleri test performance from the randomized NHS-Galleri trial across three annual screening rounds in England.</title>
      <link>https://aihealthindex.io/changelog/grail</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab90c10ee3c2977980e653e</guid>
      <pubDate>Tue, 22 Sep 2026 12:00:00 GMT</pubDate>
      <category>Clinical evidence</category>
      <category>Diagnostics &amp; Genomics</category>
      <description><![CDATA[<p>Nature Medicine published Galleri test performance from the randomized NHS-Galleri trial across three annual screening rounds in England. Specificity ranged from 99.50% to 99.60% and cancer signal origin accuracy from 91.1% to 93.6%, while positive predictive value fell from 58.0% to 50.4% to 45.8% across rounds. Episode sensitivity was 26.7% to 37.2% for all cancers and 47.6% to 63.4% for 12 prespecified types.</p><p><strong>Why it matters:</strong> This is peer reviewed randomized trial evidence in an intended use population, and the falling predictive value in later rounds bears on the cost of repeat annual screening. The data were first presented at ASCO in May 2026, so the change is the peer reviewed publication.</p><p>Impact: Medium. Verification: Verified. Type: Clinical evidence.</p><p>Evidence: <a href="https://www.nature.com/articles/s41591-026-04652-8">Peer-reviewed publication</a></p><p>Source: <a href="https://aihealthindex.io/changelog/grail">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Enzo Health: Enzo shipped Handoff Summary, a pre visit screen that brings together the patient's context and clinical focus, the alerts and…</title>
      <link>https://aihealthindex.io/changelog/enzo-health</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab90c10ee3c2977980e653d</guid>
      <pubDate>Tue, 22 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Ambient Scribes</category>
      <description><![CDATA[<p>Enzo shipped Handoff Summary, a pre visit screen that brings together the patient's context and clinical focus, the alerts and requirements for that visit, and, for Enzo EHR customers, every care plan change since the last visit. It opens in one tap from the schedule or the patient profile and keeps earlier summaries attached. It is available to both Enzo Scribe point solution customers and Enzo EHR customers.</p><p><strong>Why it matters:</strong> Home health agencies evaluating a scribe can see the product now covers visit preparation as well as documentation. The care plan change view only applies to agencies running Enzo EHR, so Scribe only buyers get a narrower version.</p><p>Impact: Medium. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://www.enzo.health/updates">Vendor documentation</a></p><p>Source: <a href="https://aihealthindex.io/changelog/enzo-health">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Doximity Ask: Doximity published Bedside Bench, an open source clinical AI benchmark of 500 cases across 10 sub benchmarks, including drug safety…</title>
      <link>https://aihealthindex.io/changelog/doximity-ask</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab90c10ee3c2977980e653c</guid>
      <pubDate>Tue, 22 Sep 2026 12:00:00 GMT</pubDate>
      <category>Clinical evidence</category>
      <category>Clinical Reference &amp; Evidence</category>
      <category>Healthcare Administrative Automation</category>
      <category>Clinical Decision Support</category>
      <description><![CDATA[<p>Doximity published Bedside Bench, an open source clinical AI benchmark of 500 cases across 10 sub benchmarks, including drug safety, guideline adherence, landmark trials, hallucination and false premises, health equity and diagnostic safety. The 250 case training split and the grading rubrics are public on Hugging Face, and the test split is held out. Bedside Bench is one of the domain benchmarks in Fireworks' Specialized Intelligence Index, and Doximity states that Doximity Ask ranked first against frontier models when Fireworks graded it.</p><p><strong>Why it matters:</strong> Buyers get a public rubric they can run against Doximity Ask and competing clinical reference tools. The ranking is stated without published scores and the benchmark was written by Doximity, so ask for the per benchmark numbers before relying on it.</p><p>Impact: Medium. Verification: Verified. Type: Clinical evidence.</p><p>Evidence: <a href="https://www.businesswire.com/news/home/20260922780582/en/Doximity-Named-Leading-Clinical-AI-Benchmark-in-Fireworks-Cross-Industry-Index">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/doximity-ask">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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    <item>
      <title>Cynerio's medical device security now ships inside Axonius for Healthcare, and cynerio.com redirects there.</title>
      <link>https://aihealthindex.io/changelog/cynerio</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab90c10ee3c2977980e653b</guid>
      <pubDate>Tue, 22 Sep 2026 12:00:00 GMT</pubDate>
      <category>EHR / interoperability</category>
      <category>Healthcare Cybersecurity</category>
      <category>Hospital &amp; Unit Operations</category>
      <description><![CDATA[<p>Cynerio's medical device security now ships inside Axonius for Healthcare, and cynerio.com redirects there. Axonius release 9.0.7 lets the TRIMEDX adapter connect through the TRIMEDX Client Inventory (v5) API alongside the older MDSP Inventory API, and adds a Network Inspectors page to the Cyber-Physical Assets module for provisioning and tracking virtual network inspector appliances by site.</p><p><strong>Why it matters:</strong> Health systems whose clinical engineering inventory runs through TRIMEDX can connect on its current API and keep biomedical asset and security records in one inventory. The inspector page is an administrative convenience for sites using passive network sensors.</p><p>Impact: Low. Verification: Verified. Type: EHR / interoperability.</p><p>Evidence: <a href="https://docs.axonius.com/changelog/release-notes-907">Vendor documentation</a></p><p>Source: <a href="https://aihealthindex.io/changelog/cynerio">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Atropos Health states it expanded its federated Atropos Evidence Network to cover over 330 million U.S. patients, including more than 150…</title>
      <link>https://aihealthindex.io/changelog/atropos-health</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab90c10ee3c2977980e653a</guid>
      <pubDate>Tue, 22 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Clinical Reference &amp; Evidence</category>
      <category>Clinical Trials AI</category>
      <category>Clinical Decision Support</category>
      <description><![CDATA[<p>Atropos Health states it expanded its federated Atropos Evidence Network to cover over 330 million U.S. patients, including more than 150 million EHR records with clinical notes, and added imaging and omics data linked to clinical outcomes and mortality through data partners including Norstella, Arcadia and OneMedNet. The network is queried through ChatRWD, Green Button and GENEVA OS, with the Real World Fitness Score grading data quality per question. The company claims temporal queries run up to 50 times faster and 30 times cheaper than traditional analytics; no method for that comparison is published.</p><p><strong>Why it matters:</strong> Health systems and life sciences teams generating real world evidence can now study questions that need imaging or genomic context alongside EHR and claims data. The speed and cost figures are vendor claims without a stated baseline, so ask for the comparison behind them.</p><p>Impact: Medium. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://www.businesswire.com/news/home/20260922102002/en/Atropos-Health-Scales-Federated-Evidence-Network-with-Multimodal-Data-Partners-to-Accelerate-Health-Analytics-and-AI-Model-Development">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/atropos-health">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Syllable release 26.9.22 added Insights Reports, a workflow detail view for reviewing analyzed results, configuration and session context…</title>
      <link>https://aihealthindex.io/changelog/syllable</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab85e9bd92e5616ac6dc813</guid>
      <pubDate>Tue, 22 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Patient Voice Agents</category>
      <category>Healthcare Administrative Automation</category>
      <category>RCM &amp; Prior Auth AI</category>
      <description><![CDATA[<p>Syllable release 26.9.22 added Insights Reports, a workflow detail view for reviewing analyzed results, configuration and session context, and Experiments, which splits live traffic across weighted voice agent variants and compares the results by session. The release also fixed voicemail delivery for carriers with short recording windows.</p><p><strong>Why it matters:</strong> Experiments turn agent changes into measured tests on real calls. Health systems should agree on the outcome being tested, such as completed scheduling, and on how patients are informed, before splitting live patient traffic between variants.</p><p>Impact: Medium. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://syllable.ai/release-notes/version-26.9.22">Vendor documentation</a></p><p>Source: <a href="https://aihealthindex.io/changelog/syllable">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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    <item>
      <title>Relatient extended the self scheduling and call center scheduling tools in its Dash platform to behavioral health providers, adding secure…</title>
      <link>https://aihealthindex.io/changelog/relatient</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab85e9bd92e5616ac6dc812</guid>
      <pubDate>Tue, 22 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Patient Voice Agents</category>
      <category>Healthcare Administrative Automation</category>
      <description><![CDATA[<p>Relatient extended the self scheduling and call center scheduling tools in its Dash platform to behavioral health providers, adding secure self service booking and automated appointment management. Relatient cites one behavioral health customer where 60 percent of self scheduled appointments came from new patients and 47 percent of booked appointments were seen within three days.</p><p><strong>Why it matters:</strong> Behavioral health scheduling carries privacy and intake requirements that general scheduling tools handle poorly. Organizations should ask which intake steps are automated and how sensitive appointment types are kept out of reminders and call center scripts.</p><p>Impact: Medium. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://www.businesswire.com/news/home/20260922587403/en/Relatient-Expands-Intelligent-Scheduling-to-Behavioral-Health-Helping-Organizations-Scale-Patient-Access-for-High-Demand">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/relatient">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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    <item>
      <title>Deciphex launched CipherX, a pathology AI engine that pairs foundation models with a semantic layer translating their representations into…</title>
      <link>https://aihealthindex.io/changelog/deciphex</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab85e9bd92e5616ac6dc811</guid>
      <pubDate>Tue, 22 Sep 2026 12:00:00 GMT</pubDate>
      <category>Model / architecture</category>
      <category>Digital Pathology AI</category>
      <category>Drug Discovery AI</category>
      <category>Clinical Trials AI</category>
      <description><![CDATA[<p>Deciphex launched CipherX, a pathology AI engine that pairs foundation models with a semantic layer translating their representations into named, pathologist validated tissue signatures. Deciphex states CipherX is in production in its Diagnexia clinical diagnostic service and its Patholytix research business, and reports negative predictive values of 99.85 percent for adenocarcinoma and 98.76 percent for melanoma in production, with every Diagnexia case signed out by a pathologist.</p><p><strong>Why it matters:</strong> Labs using Diagnexia get CipherX inside the service rather than as a separate purchase. The predictive values are vendor reported, so ask for the case mix and prevalence behind them and which signatures are used in clinical sign out today rather than research only.</p><p>Impact: High. Verification: Verified. Type: Model / architecture.</p><p>Evidence: <a href="https://www.deciphex.com/news/deciphex-launches-cipherx">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/deciphex">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Cohere Health published performance results for Cohere Capture, which extracts HEDIS gap closures and denominator exclusions from clinical…</title>
      <link>https://aihealthindex.io/changelog/cohere-health</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab85e9bd92e5616ac6dc810</guid>
      <pubDate>Tue, 22 Sep 2026 12:00:00 GMT</pubDate>
      <category>Clinical evidence</category>
      <category>RCM &amp; Prior Auth AI</category>
      <category>Clinical Decision Support</category>
      <description><![CDATA[<p>Cohere Health published performance results for Cohere Capture, which extracts HEDIS gap closures and denominator exclusions from clinical data a health plan already holds, including prior authorization notes, imaging reports and EHR data. Cohere reports an average 15 percent improvement in Stars performance per measure, 107 gaps closed per 1,000 members with records, and a minimum 5 to 1 return on a pay for performance model.</p><p><strong>Why it matters:</strong> These figures are vendor reported and the release does not describe how they were measured. Plans should ask for the method and baseline behind the 15 percent figure, and how much of the lift comes from prior authorization records Cohere already sees as the plan's utilization management vendor.</p><p>Impact: Medium. Verification: Verified. Type: Clinical evidence.</p><p>Evidence: <a href="https://www.coherehealth.com/news/cohere-capture-hedis-gap-closure-medicare-advantage">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/cohere-health">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Ambience Healthcare: Ambience described a change to its clinical speech recognition pipeline from a mini batch ensemble to a rolling window ensemble, which…</title>
      <link>https://aihealthindex.io/changelog/ambience-healthcare</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab85e9bd92e5616ac6dc80f</guid>
      <pubDate>Tue, 22 Sep 2026 12:00:00 GMT</pubDate>
      <category>Model / architecture</category>
      <category>Ambient Scribes</category>
      <category>RCM &amp; Prior Auth AI</category>
      <category>Autonomous Medical Coding</category>
      <description><![CDATA[<p>Ambience described a change to its clinical speech recognition pipeline from a mini batch ensemble to a rolling window ensemble, which keeps recent audio in scope so a reconciliation model can revise earlier transcript segments as more audio arrives. Ambience reports keyword error fell 16 percent against the previous design on a 226 encounter evaluation spanning 28 specialties and 15 clinicians, at the cost of a median processing cycle roughly 40 percent longer.</p><p><strong>Why it matters:</strong> Errors on drug names, dosages and negations are what make an ambient note unsafe to sign, which is why keyword error is the figure to watch. The evaluation is the vendor's own and spreads 226 encounters across 28 specialties, so ask whether the gain holds in your highest volume specialties.</p><p>Impact: Medium. Verification: Verified. Type: Model / architecture.</p><p>Evidence: <a href="https://www.ambiencehealthcare.com/blog/beyond-the-first-guess-rolling-window-ensembles-for-clinical-asr">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/ambience-healthcare">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Alcidion: Miya Precision 7.11.0 introduces a three tier restricted access model for patient records: full access, break glass access that requires…</title>
      <link>https://aihealthindex.io/changelog/alcidion</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab90c10ee3c2977980e6539</guid>
      <pubDate>Mon, 21 Sep 2026 12:00:00 GMT</pubDate>
      <category>Security / compliance</category>
      <category>Hospital &amp; Unit Operations</category>
      <category>Clinical Decision Support</category>
      <category>Health System AI Platforms</category>
      <description><![CDATA[<p>Miya Precision 7.11.0 introduces a three tier restricted access model for patient records: full access, break glass access that requires justification via an individual PIN with audit tracking, and no access. Alcidion states the design supports NHS safeguarding principles.</p><p><strong>Why it matters:</strong> Privacy and information governance teams get record level access control with an audited break glass path, which matters for restricted and safeguarding sensitive patients.</p><p>Impact: Low. Verification: Verified. Type: Security / compliance.</p><p>Evidence: <a href="https://www.alcidion.com/news/miya-precision-7-11-0/">Vendor documentation</a></p><p>Source: <a href="https://aihealthindex.io/changelog/alcidion">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Alcidion's Miya Precision 7.11.0 adds a native inpatient admissions workflow, completing its admission, transfer, leave and discharge set…</title>
      <link>https://aihealthindex.io/changelog/alcidion</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab90c10ee3c2977980e6538</guid>
      <pubDate>Mon, 21 Sep 2026 12:00:00 GMT</pubDate>
      <category>EHR / interoperability</category>
      <category>Hospital &amp; Unit Operations</category>
      <category>Clinical Decision Support</category>
      <category>Health System AI Platforms</category>
      <description><![CDATA[<p>Alcidion's Miya Precision 7.11.0 adds a native inpatient admissions workflow, completing its admission, transfer, leave and discharge set, with one way or two way integration to the Patient Administration System so clinicians no longer need to open the PAS. The release also adds Miya Vitals, for capturing observations on charts defined per care area such as ICU, ED and general wards with validation checks and warning thresholds, and Dynamic Fluid Balance Management, which calculates fluid restriction limits from patient weight.</p><p><strong>Why it matters:</strong> Trusts running a separate PAS can manage the full inpatient encounter in Miya Precision while keeping the PAS in sync, which cuts double entry. Vitals capture is manual entry only in this release; Alcidion states capture from bedside monitors is planned for a future release.</p><p>Impact: Medium. Verification: Verified. Type: EHR / interoperability.</p><p>Evidence: <a href="https://www.alcidion.com/news/miya-precision-7-11-0/">Vendor documentation</a></p><p>Source: <a href="https://aihealthindex.io/changelog/alcidion">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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    <item>
      <title>Zus Health: Zus refreshed the code sets behind its automatic tagging of specially regulated records against current VSAC value sets.</title>
      <link>https://aihealthindex.io/changelog/zus-health</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab85e9bd92e5616ac6dc80e</guid>
      <pubDate>Mon, 21 Sep 2026 12:00:00 GMT</pubDate>
      <category>Security / compliance</category>
      <category>Healthcare Administrative Automation</category>
      <category>Clinical Summarization &amp; Chart Review</category>
      <category>Value Based Care Intelligence</category>
      <description><![CDATA[<p>Zus refreshed the code sets behind its automatic tagging of specially regulated records against current VSAC value sets. Contraceptive management records now receive the SEX specially regulated label alongside abortion and gender affirming care, the categories covered under California AB 352. Data customers had already written to Zus was retagged under the updated sets.</p><p><strong>Why it matters:</strong> First party records that match these codes also receive the Restricted label, which Zus says withholds them from other builders, from Lens summarization, and from CommonWell and Carequality responses. Third party records get the specially regulated label only, so customers should confirm their own downstream systems honor it.</p><p>Impact: Medium. Verification: Verified. Type: Security / compliance.</p><p>Evidence: <a href="https://docs.zushealth.com/changelog/september-21-2026-restricted-data-tagging-updates-for-abortion-gender-affirming-and-contraceptive-care">Vendor documentation</a></p><p>Source: <a href="https://aihealthindex.io/changelog/zus-health">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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    <item>
      <title>Upheal added voice input to Upheal Assistant, so clinicians can speak requests instead of typing them.</title>
      <link>https://aihealthindex.io/changelog/upheal</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab85e9bd92e5616ac6dc80d</guid>
      <pubDate>Mon, 21 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Behavioral Health AI</category>
      <category>Ambient Scribes</category>
      <category>Healthcare Administrative Automation</category>
      <description><![CDATA[<p>Upheal added voice input to Upheal Assistant, so clinicians can speak requests instead of typing them. Reports, still in beta, can now be downloaded as an image or a spreadsheet containing headline figures and full chart values, and any report can be opened in the Assistant for questions about it.</p><p><strong>Why it matters:</strong> The Assistant now reaches practice reporting as well as session notes. Practices that hand report data to bookkeepers or billers should check what the spreadsheet export contains, since that data now leaves the platform in one step.</p><p>Impact: Low. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://feedback.upheal.io/changelog/speak-to-upheal-assistant-and-get-more-out-of-reports">Vendor documentation</a></p><p>Source: <a href="https://aihealthindex.io/changelog/upheal">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Iambic Therapeutics: Iambic released Enchant v3, the third generation of the multimodal transformer behind its drug discovery platform.</title>
      <link>https://aihealthindex.io/changelog/iambic-therapeutics</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab85e9bd92e5616ac6dc80c</guid>
      <pubDate>Mon, 21 Sep 2026 12:00:00 GMT</pubDate>
      <category>Model / architecture</category>
      <category>Drug Discovery AI</category>
      <description><![CDATA[<p>Iambic released Enchant v3, the third generation of the multimodal transformer behind its drug discovery platform. Iambic states the model has 41 billion parameters, was pretrained on 4.5 trillion tokens, and covers more than 6,000 molecular properties across 16 biomedical data modalities using a mixture of experts architecture. Iambic says it will be used on internal and partner programs.</p><p><strong>Why it matters:</strong> Enchant v3 is the model partners get when they work with Iambic, so its prediction accuracy is the thing being bought. Iambic says scaling has held across three generations, including on endpoints with sparse data. Ask for the benchmark results in the Enchant v3 report and how they hold on targets with little training data.</p><p>Impact: High. Verification: Verified. Type: Model / architecture.</p><p>Evidence: <a href="https://www.iambic.ai/post/iambic-launches-enchant-v3---molecular-superintelligence-designed-to-advance-end-to-end-drug-discovery-development">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/iambic-therapeutics">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>ClosedLoop, the healthcare data science and predictive analytics company, no longer sells a healthcare product.</title>
      <link>https://aihealthindex.io/changelog</link>
      <guid isPermaLink="false">aihealthindex.io:change:6ab1706b20ec9db8cbfa9e9f</guid>
      <pubDate>Mon, 21 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product sunset</category>
      <description><![CDATA[<p>ClosedLoop, the healthcare data science and predictive analytics company, no longer sells a healthcare product. Its domain now offers a workspace for team based agentic software development, with no healthcare product, page or customer route. No acquirer of the healthcare business has been announced. The date the healthcare offering ended is not published; the change was observed on 21 September 2026.</p><p><strong>Why it matters:</strong> Organizations still running ClosedLoop models for readmission, utilization or risk stratification should confirm in writing who supports those models now and what happens to their data, because the domain no longer publishes a healthcare support route. ClosedLoop no longer appears in the index's value based care lane; buyers comparing risk stratification vendors will find current options on that lane page.</p><p>Impact: High. Verification: Verified. Type: Product sunset.</p><p>Evidence: <a href="https://www.closedloop.ai/">Vendor documentation</a></p><p>Source: <a href="https://aihealthindex.io/changelog">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Upheal added a Reports section with a curated report library and five thematic dashboards for tracking practice metrics.</title>
      <link>https://aihealthindex.io/changelog/upheal</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aaeaddaaaa02078636c9cab</guid>
      <pubDate>Fri, 18 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Behavioral Health AI</category>
      <category>Ambient Scribes</category>
      <category>Healthcare Administrative Automation</category>
      <description><![CDATA[<p>Upheal added a Reports section with a curated report library and five thematic dashboards for tracking practice metrics. Users can also ask the Upheal Assistant to generate a specific chart.</p><p><strong>Why it matters:</strong> Small therapy practices usually export to spreadsheets to see how the business is doing. Charts generated on request are convenient; check that they draw on the same numbers as the fixed dashboards before using them for payer or staffing decisions. Practice reporting is a convenience layer, not a clinical capability, so it should not move an evaluation far on its own.</p><p>Impact: Low. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://feedback.upheal.io/changelog/see-your-practice-at-a-glance-with-reports-barchart">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/upheal">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>DeepHealth received FDA 510(k) clearance for Chest XRay, a computer aided detection tool built on a foundation model that detects and…</title>
      <link>https://aihealthindex.io/changelog/deephealth</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aaeaddaaaa02078636c9caa</guid>
      <pubDate>Fri, 18 Sep 2026 12:00:00 GMT</pubDate>
      <category>Regulatory / FDA</category>
      <category>Radiology &amp; Imaging AI</category>
      <category>Health System AI Platforms</category>
      <category>Hospital &amp; Unit Operations</category>
      <description><![CDATA[<p>DeepHealth received FDA 510(k) clearance for Chest XRay, a computer aided detection tool built on a foundation model that detects and localizes abnormalities on chest radiographs. It is the next version of the technology DeepHealth acquired with Gleamer, it is commercially available in the US now, and existing customers are eligible for the update.</p><p><strong>Why it matters:</strong> A foundation model clearance matters because one model covers many findings, rather than one narrow algorithm per finding. Radiology groups should ask exactly which findings the 510(k) covers, since marketing for foundation models tends to run ahead of the cleared indications.</p><p>Impact: High. Verification: Partially Verified. Type: Regulatory / FDA.</p><p>Evidence: <a href="https://www.itnonline.com/content/fda-clears-chest-x-ray-solution-deephealth">Trade press</a></p><p>Source: <a href="https://aihealthindex.io/changelog/deephealth">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Assort Health expanded its direct workflow automation for practices on NextGen Enterprise.</title>
      <link>https://aihealthindex.io/changelog/assort-health</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aaeaddaaaa02078636c9cac</guid>
      <pubDate>Thu, 17 Sep 2026 12:00:00 GMT</pubDate>
      <category>EHR / interoperability</category>
      <category>Patient Voice Agents</category>
      <description><![CDATA[<p>Assort Health expanded its direct workflow automation for practices on NextGen Enterprise. Using NextGen's Platinum API tier, Assort's AI agents can read and write appointment slots, referrals, clinical notes, chart alerts, diagnoses, procedures and payment workflows directly in the EHR.</p><p><strong>Why it matters:</strong> Write access is the line between an agent that answers the phone and one that finishes the job. Practices should confirm which of those write actions are switched on by default, and how each one appears in the NextGen audit trail.</p><p>Impact: High. Verification: Partially Verified. Type: EHR / interoperability.</p><p>Evidence: <a href="https://www.nextgen.com/solutions/marketplace/assorthealth">Vendor documentation</a></p><p>Source: <a href="https://aihealthindex.io/changelog/assort-health">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>RadiantGraph launched Care Guidance Agents, AI voice agents that give patients with chronic conditions ongoing support: education after a…</title>
      <link>https://aihealthindex.io/changelog/radiantgraph</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aaeaddaaaa02078636c9cad</guid>
      <pubDate>Wed, 16 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Patient Voice Agents</category>
      <category>Value Based Care Intelligence</category>
      <description><![CDATA[<p>RadiantGraph launched Care Guidance Agents, AI voice agents that give patients with chronic conditions ongoing support: education after a diagnosis, daily management coaching and preventive care, with dedicated agents for musculoskeletal and behavioral health. RadiantGraph also says it has been approved for the CMS ACCESS Model, so participating providers can enroll Medicare Part B patients.</p><p><strong>Why it matters:</strong> ACCESS pays for outcomes, not activity, so any vendor in it has to show that its agents actually move blood pressure, pain or depression scores. Ask RadiantGraph which ACCESS tracks it covers and what outcome data it can hand back to a provider.</p><p>Impact: Medium. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://www.prnewswire.com/news-releases/radiantgraph-adds-care-guidance-agents-to-extend-personalized-chronic-condition-support-approved-for-cms-access-model-302879815.html">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/radiantgraph">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Upheal now lets practices invite non clinical staff such as billers and practice managers.</title>
      <link>https://aihealthindex.io/changelog/upheal</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aaeaddaaaa02078636c9cb4</guid>
      <pubDate>Tue, 15 Sep 2026 12:00:00 GMT</pubDate>
      <category>Security / compliance</category>
      <category>Behavioral Health AI</category>
      <category>Ambient Scribes</category>
      <category>Healthcare Administrative Automation</category>
      <description><![CDATA[<p>Upheal now lets practices invite non clinical staff such as billers and practice managers. Those roles cannot see clinical notes, treatment plans, transcripts or AI generated clinical content.</p><p><strong>Why it matters:</strong> Therapy notes carry some of the strictest privacy expectations in healthcare, and giving a biller full access just to reach the invoices was a real exposure. Role based access that walls off the AI generated clinical content is the right default.</p><p>Impact: Medium. Verification: Verified. Type: Security / compliance.</p><p>Evidence: <a href="https://feedback.upheal.io/changelog/invite-your-biller-or-practice-manager-to-upheal-lock">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/upheal">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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    <item>
      <title>Sorcero's Fall 2026 release adds purpose built AI solutions for field medical, medical communications, and therapeutic leadership and…</title>
      <link>https://aihealthindex.io/changelog/sorcero</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aaeaddaaaa02078636c9cb3</guid>
      <pubDate>Tue, 15 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Clinical Trials AI</category>
      <description><![CDATA[<p>Sorcero's Fall 2026 release adds purpose built AI solutions for field medical, medical communications, and therapeutic leadership and launch teams, plus a Medical Strategy solution for tracking scientific resonance. It also introduces Sorcero Wizard, a conversational layer for working with the data, and analytics views that show data ingestion and intelligence generation in real time.</p><p><strong>Why it matters:</strong> Medical affairs teams work under strict rules about what they can say and to whom, so governance is the feature that matters here. Ask how the platform separates what field medical can see from what commercial teams can see.</p><p>Impact: Medium. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://www.sorcero.com/sorceros-fall-2026-release-gives-every-function-within-medical-affairs-a-purpose-built-ai-solution-on-one-governed-ai-and-data-platform">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/sorcero">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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    <item>
      <title>Knowtex reported results from a US Department of Veterans Affairs assessment of its ambient scribe at the Kansas City VA, covering 18…</title>
      <link>https://aihealthindex.io/changelog/knowtex</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aaeaddaaaa02078636c9cb2</guid>
      <pubDate>Tue, 15 Sep 2026 12:00:00 GMT</pubDate>
      <category>Clinical evidence</category>
      <category>Ambient Scribes</category>
      <description><![CDATA[<p>Knowtex reported results from a US Department of Veterans Affairs assessment of its ambient scribe at the Kansas City VA, covering 18 primary care providers: most saved one to two hours of after hours work, and patient experience scores rose nearly three points to 95.8 percent. In the same announcement Knowtex launched a Frontier AI Lab for Healthcare and KnowBench, an internal benchmark on which it scores its own platform at 97.99 percent.</p><p><strong>Why it matters:</strong> The VA assessment is the part worth weight: an outside health system, working clinicians and patient scores. KnowBench is Knowtex testing its own product, so treat that figure as marketing until someone else runs it. Eighteen providers at one site, reported by the vendor rather than published, is too small to carry an evaluation on its own.</p><p>Impact: Medium. Verification: Partially Verified. Type: Clinical evidence.</p><p>Evidence: <a href="https://www.prnewswire.com/news-releases/knowtex-launches-the-frontier-ai-lab-for-healthcare-bringing-research-grade-clinical-ai-to-health-systems-to-maximize-intelligence-per-patient-encounter-302878575.html">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/knowtex">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>AliveCor launched KardiaACCESS, its program under the CMS ACCESS Model, the 10 year Medicare initiative for technology supported chronic…</title>
      <link>https://aihealthindex.io/changelog/alivecor</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aaeaddaaaa02078636c9cb1</guid>
      <pubDate>Tue, 15 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Remote Monitoring &amp; Chronic Care</category>
      <category>Diagnostics &amp; Genomics</category>
      <description><![CDATA[<p>AliveCor launched KardiaACCESS, its program under the CMS ACCESS Model, the 10 year Medicare initiative for technology supported chronic care. Eligible Original Medicare beneficiaries get clinician guided care and AliveCor's connected devices for managing blood pressure, diabetes and heart health, at no out of pocket cost.</p><p><strong>Why it matters:</strong> This is AliveCor becoming a care provider under Medicare, not only a device maker. Clinicians referring patients should understand who is accountable for the outcomes ACCESS pays on, and how AliveCor's clinicians coordinate with the patient's own doctor.</p><p>Impact: Medium. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://www.globenewswire.com/news-release/2026/09/15/3362311/0/en/alivecor-launches-kardiaaccess-a-medicare-covered-program-built-to-improve-blood-pressure-diabetes-and-heart-health.html">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/alivecor">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Andros was acquired by Medallion.</title>
      <link>https://aihealthindex.io/changelog</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aaeaddaaaa02078636c9cb0</guid>
      <pubDate>Tue, 15 Sep 2026 12:00:00 GMT</pubDate>
      <category>Acquisition / corporate</category>
      <description><![CDATA[<p>Andros was acquired by Medallion. Andros customers will move onto Medallion's AI credentialing platform, which adds automated primary source collection, AI agents for provider outreach and real time status tracking.</p><p><strong>Why it matters:</strong> Health plans that chose Andros for its NCQA certified verification now have a new platform underneath it. Ask for the transition timeline in writing, and whether NCQA certification carries across without a gap.</p><p>Impact: Medium. Verification: Verified. Type: Acquisition / corporate.</p><p>Evidence: <a href="https://www.prnewswire.com/news-releases/medallion-acquires-andros-to-expand-ai-native-credentialing-across-health-plans-and-provider-organizations-302878839.html">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Hello Patient acquired Converse Health, adding AI agents that handle the document and chart work around a visit.</title>
      <link>https://aihealthindex.io/changelog/hello-patient</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aaeaddaaaa02078636c9caf</guid>
      <pubDate>Tue, 15 Sep 2026 12:00:00 GMT</pubDate>
      <category>Acquisition / corporate</category>
      <category>Patient Voice Agents</category>
      <category>Healthcare Administrative Automation</category>
      <category>RCM &amp; Prior Auth AI</category>
      <description><![CDATA[<p>Hello Patient acquired Converse Health, adding AI agents that handle the document and chart work around a visit. The combined platform reads incoming faxes, matches or creates the patient record, files documents in the EHR and then follows up with the patient by call or text. Hello Patient integrates with ModMed, athenahealth and eClinicalWorks.</p><p><strong>Why it matters:</strong> Most practice automation stops at the phone, while the paperwork behind a referral still lands on staff. Buyers should ask how the agent handles a fax it cannot match to a patient, because a misfiled clinical document is a patient safety problem, not just an admin one.</p><p>Impact: Medium. Verification: Verified. Type: Acquisition / corporate.</p><p>Evidence: <a href="https://www.hellopatient.com/blog/news/hello-patient-acquires-converse-health">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/hello-patient">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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    <item>
      <title>AZmed received its sixth FDA clearance, for AZchest to detect and localize pneumothorax and pleural effusion on chest radiographs.</title>
      <link>https://aihealthindex.io/changelog/azmed</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aaeaddaaaa02078636c9cae</guid>
      <pubDate>Tue, 15 Sep 2026 12:00:00 GMT</pubDate>
      <category>Regulatory / FDA</category>
      <category>Radiology &amp; Imaging AI</category>
      <category>Clinical Decision Support</category>
      <description><![CDATA[<p>AZmed received its sixth FDA clearance, for AZchest to detect and localize pneumothorax and pleural effusion on chest radiographs. That brings its Rayvolve suite to eight FDA cleared findings, and AZchest can now flag up to five findings on a single chest image.</p><p><strong>Why it matters:</strong> Pneumothorax is a time critical miss, which is why this clearance matters more than the count. AZmed cites reading time reductions of up to 31 percent for readers outside thoracic radiology; that is the group to test it with, since specialist readers gain least.</p><p>Impact: High. Verification: Verified. Type: Regulatory / FDA.</p><p>Evidence: <a href="https://www.azmed.co/news-post/azmed-receives-its-6th-fda-clearance-taking-rayvolve-to-eight-fda-cleared-findings-across-msk">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/azmed">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Veracyte acquired Convergent Genomics, adding the UroAmp urine tumor DNA test to its urology portfolio.</title>
      <link>https://aihealthindex.io/changelog/veracyte</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aaeaddaaaa02078636c9cb7</guid>
      <pubDate>Mon, 14 Sep 2026 12:00:00 GMT</pubDate>
      <category>Acquisition / corporate</category>
      <category>Diagnostics &amp; Genomics</category>
      <category>Clinical Decision Support</category>
      <description><![CDATA[<p>Veracyte acquired Convergent Genomics, adding the UroAmp urine tumor DNA test to its urology portfolio. Veracyte can now offer genomic testing from urine, tissue and blood across bladder cancer care.</p><p><strong>Why it matters:</strong> A urine test can help monitor bladder cancer between cystoscopies, the procedure patients most want to avoid. Urologists should ask how UroAmp results will be reported alongside Veracyte's existing tests, and whether ordering stays the same during the integration.</p><p>Impact: Medium. Verification: Verified. Type: Acquisition / corporate.</p><p>Evidence: <a href="https://investor.veracyte.com/news-releases/news-release-details/veracyte-acquires-convergent-genomics-expanding-its-urology">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/veracyte">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Oracle Health Clinical AI Agent: Oracle made its Clinical AI Agent available to inpatient nurses in the US.</title>
      <link>https://aihealthindex.io/changelog/oracle-health-clinical-ai-agent</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aaeaddaaaa02078636c9cb6</guid>
      <pubDate>Mon, 14 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Ambient Scribes</category>
      <description><![CDATA[<p>Oracle made its Clinical AI Agent available to inpatient nurses in the US. Nurses get voice driven chart navigation, acute nursing summaries and voice enabled discrete charting inside the Oracle Health Foundation EHR.</p><p><strong>Why it matters:</strong> Ambient AI has so far been sold to physicians, while nurses do more of the documentation and have had less help. Discrete charting by voice is the piece to test, because structured data that lands in the wrong field is harder to catch than a messy note.</p><p>Impact: High. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://www.oracle.com/news/announcement/oracle-health-clinical-ai-agent-helps-nurses-alleviate-documentation-burden-and-streamline-care-2026-09-14/">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/oracle-health-clinical-ai-agent">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Abridge launched pre bill review for clinical documentation integrity, coding and revenue cycle teams.</title>
      <link>https://aihealthindex.io/changelog/abridge</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aaeaddaaaa02078636c9cb5</guid>
      <pubDate>Mon, 14 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Ambient Scribes</category>
      <category>RCM &amp; Prior Auth AI</category>
      <category>Clinical Decision Support</category>
      <description><![CDATA[<p>Abridge launched pre bill review for clinical documentation integrity, coding and revenue cycle teams. It checks inpatient claims before submission, comparing the coded diagnoses and DRG against what the clinical record supports, including what was captured in the encounter, and surfaces discrepancies with the evidence. Abridge does not change documentation, codes or claim status; the CDI team decides what to hold, correct or release.</p><p><strong>Why it matters:</strong> This takes Abridge from the exam room into the revenue cycle, where CDI vendors have worked for years. The advantage it claims is the encounter itself: a coder can see what was actually discussed, not just what was written. Ask how discrepancies are ranked, and how often a flag leads to a correction rather than a physician query.</p><p>Impact: High. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://www.abridge.com/press-release/pre-bill-review-for-cdi-and-coding-teams">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/abridge">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Aignostics released PathoSearch in early access, a visual search engine for pathology: from a screenshot of a region of interest on an H…</title>
      <link>https://aihealthindex.io/changelog/aignostics</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aa5b27795f1c7683c18cf6f</guid>
      <pubDate>Sat, 12 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Digital Pathology AI</category>
      <category>Drug Discovery AI</category>
      <category>Clinical Trials AI</category>
      <description><![CDATA[<p>Aignostics released PathoSearch in early access, a visual search engine for pathology: from a screenshot of a region of interest on an H and E slide it retrieves morphologically similar, diagnosed reference cases so a pathologist can build a differential in minutes. Search runs on embeddings from Atlas 2, Aignostics' pathology foundation model co developed with Mayo Clinic, against a curated multi center reference set of more than 310,000 whole slide images from over 35,000 cases spanning more than 300 diagnostic entities across 27 organs, covering thoracic, digestive, soft tissue and bone, female genital, and urinary and male genital cancers at launch. The first integration is live inside Techcyte's Fusion AP slide viewer, where a selected region is passed to PathoSearch without export or upload. PathoSearch is free during early access, by waitlist, and is labeled research use only, not for diagnostic procedures.</p><p><strong>Why it matters:</strong> Rare and complex cases are where a pathologist reaches for a textbook or a paid consult, and image similarity search against a diagnosed reference set is a plausible replacement for the first of those. The research use only label is the operative constraint: this cannot be part of a signed out diagnosis today, and a lab evaluating it should treat the Fusion AP integration as the way to try it inside the workflow rather than as a clinical deployment.</p><p>Impact: Medium. Verification: Partially Verified. Type: Product / capability.</p><p>Evidence: <a href="https://www.prnewswire.com/news-releases/aignostics-launches-pathosearch-a-visual-search-engine-for-pathology-cases-302876588.html">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/aignostics">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Parlance made its IT help desk intelligent virtual assistant available on the ServiceNow Store, alongside a new identity verification step…</title>
      <link>https://aihealthindex.io/changelog/parlance</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aa5b27795f1c7683c18cf6e</guid>
      <pubDate>Wed, 09 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Patient Voice Agents</category>
      <category>Healthcare Administrative Automation</category>
      <description><![CDATA[<p>Parlance made its IT help desk intelligent virtual assistant available on the ServiceNow Store, alongside a new identity verification step for the voice channel: for sensitive requests such as a password reset, the assistant reads a one time code to the caller, who confirms it in Cisco Duo or another enterprise authenticator before the action proceeds. Parlance cites industry estimates that password resets drive 20 to 50 percent of health system IT help desk call volume.</p><p><strong>Why it matters:</strong> The Duo step is the part with security consequence: an unverified push or an SMS code confirms that someone approved something, while a code read on the live call and confirmed in the authenticator ties the approval to that caller and that request, which closes the social engineering path that help desk voice bots opened. Health systems on ServiceNow can now evaluate this from the Store rather than through a custom integration.</p><p>Impact: Medium. Verification: Partially Verified. Type: Product / capability.</p><p>Evidence: <a href="https://www.prnewswire.com/news-releases/parlance-brings-verified-push-notification-security-to-health-system-it-help-desks-on-servicenow-store-302872636.html">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/parlance">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Primaa and PathPresenter announced completion of their joint validation study of Cleo Skin, Primaa's dermatopathology AI, running inside…</title>
      <link>https://aihealthindex.io/changelog/primaa</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aa5b27795f1c7683c18cf6d</guid>
      <pubDate>Tue, 08 Sep 2026 12:00:00 GMT</pubDate>
      <category>Clinical evidence</category>
      <category>Digital Pathology AI</category>
      <category>Diagnostics &amp; Genomics</category>
      <description><![CDATA[<p>Primaa and PathPresenter announced completion of their joint validation study of Cleo Skin, Primaa's dermatopathology AI, running inside PathPresenter's FDA cleared clinical viewer. The study covered a realistic case mix of melanoma, naevus, squamous cell carcinoma, basal cell carcinoma and benign lesions, and the companies report faster and more consistent diagnostic reporting when the AI populates structured reporting fields inside the viewer. Interim phase one results PathPresenter published in March reported a 25 percent reduction in analysis time and a 6 percent improvement in diagnostic accuracy with the model, with higher interobserver agreement on lesion classification.</p><p><strong>Why it matters:</strong> The finding worth holding onto is that the gains came from the AI being inside the viewer rather than beside it, which is the deployment shape most labs still have not achieved. The evidence is vendor and partner reported, with the population and endpoints described at summary level, so treat it as a workflow study rather than a diagnostic accuracy trial until the full results are published, and ask which of the interim numbers held at completion.</p><p>Impact: Medium. Verification: Partially Verified. Type: Clinical evidence.</p><p>Evidence: <a href="https://www.pathpresenter.com/primaa-and-pathpresenter-introduce-fully-integrated-ai-workflows-for-dermatopathology/">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/primaa">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Maverick Medical AI announced a proprietary Clinical to Revenue Foundation Model that now powers its two products: CodeAgent, which…</title>
      <link>https://aihealthindex.io/changelog/maverick-medical-ai</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aa5b27795f1c7683c18cf6c</guid>
      <pubDate>Tue, 08 Sep 2026 12:00:00 GMT</pubDate>
      <category>Model / architecture</category>
      <category>Autonomous Medical Coding</category>
      <category>RCM &amp; Prior Auth AI</category>
      <description><![CDATA[<p>Maverick Medical AI announced a proprietary Clinical to Revenue Foundation Model that now powers its two products: CodeAgent, which engages physicians at the point of care to flag missing documentation, coding opportunities, medical necessity gaps, modifier errors, MIPS requirements and payer specific risks before a note is finalized, and mCoder, which generates billing ready codes from that clinical context while further agents validate payer policy and compliance rules before a claim goes out. Maverick says the model learns revenue cycle intelligence common across specialties while adapting to specialty specific workflows, and reports 85 percent or better direct to bill performance in production.</p><p><strong>Why it matters:</strong> A vendor claiming a foundation model for coding is making a model disclosure claim, and the release gives a buyer nothing to check it against: no architecture, training data, evaluation set or specialty breakdown. The direct to bill figure is the number to test on the institution's own claims mix, and the CodeAgent behavior is the one to watch clinically, since a system that prompts physicians for coding opportunities at the point of care sits close to the line compliance teams draw around upcoding.</p><p>Impact: Medium. Verification: Partially Verified. Type: Model / architecture.</p><p>Evidence: <a href="https://www.globenewswire.com/news-release/2026/09/08/3358090/0/en/maverick-medical-ai-brings-revenue-certainty-to-the-hospital-revenue-cycle.html">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/maverick-medical-ai">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>Canary Speech: Canary Ambient for Physicians is generally available inside Microsoft Dragon Copilot, listed on the Microsoft Marketplace as part of the…</title>
      <link>https://aihealthindex.io/changelog/canary-speech</link>
      <guid isPermaLink="false">aihealthindex.io:change:6aa5b27795f1c7683c18cf6b</guid>
      <pubDate>Fri, 04 Sep 2026 12:00:00 GMT</pubDate>
      <category>EHR / interoperability</category>
      <category>Behavioral Health AI</category>
      <category>Clinical Decision Support</category>
      <category>Remote Monitoring &amp; Chronic Care</category>
      <description><![CDATA[<p>Canary Ambient for Physicians is generally available inside Microsoft Dragon Copilot, listed on the Microsoft Marketplace as part of the Dragon Copilot AI Apps and Agents program Microsoft opened on 21 August. Inside the Dragon workflow, Canary analyses the acoustic and linguistic properties of the recorded encounter to surface screening signals for mild cognitive impairment and Alzheimer's disease (Canary Cognitive) and for depression and anxiety (Canary Behavioral), with no separate application or added step during the visit. Canary describes the output as clinical decision support for a clinician to interpret, not a diagnosis, and states that Marketplace listing is not self service: enablement still goes through Canary for licensing and deployment.</p><p><strong>Why it matters:</strong> The change is distribution, not the model: a health system already on Dragon Copilot can now procure and deploy voice biomarker screening through a channel its IT and legal teams have already approved, which is the step that has kept this category in pilots. The questions Canary itself says to ask are the right ones, and they belong in the contract: intended use, patient consent for biomarker analysis, audio retention and deletion, whether encounter audio trains vendor models, and performance across accent, age and language.</p><p>Impact: High. Verification: Verified. Type: EHR / interoperability.</p><p>Evidence: <a href="https://canaryspeech.com/blog/canary-ambient-now-available-in-dragon-copilot/">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/canary-speech">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>IQVIA launched Predictive Clinical Development, a suite covering site selection and study design, an automated start up path it calls Push…</title>
      <link>https://aihealthindex.io/changelog/iqvia</link>
      <guid isPermaLink="false">aihealthindex.io:change:6a9c312c04c538181acf1b41</guid>
      <pubDate>Thu, 03 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Clinical Trials AI</category>
      <category>Clinical Decision Support</category>
      <description><![CDATA[<p>IQVIA launched Predictive Clinical Development, a suite covering site selection and study design, an automated start up path it calls Push Button Start-Up, and real time data cleaning aimed at shortening the gap to database lock.</p><p><strong>Why it matters:</strong> Each of the three targets a different well known delay, and the one worth interrogating is real time data cleaning, because database lock timelines are usually held up by query resolution rather than by query generation. Sponsors evaluating this should ask which of the three has a measured effect on an actual study rather than a modeled one.</p><p>Impact: High. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://www.iqvia.com/newsroom/2026/09/iqvia-predictive-clinical-development-provides-sponsors-with-significant-efficiencies">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/iqvia">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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      <title>BrainCheck added BrainCheck Screen, a pre screening tool that identifies which patients need fuller cognitive testing.</title>
      <link>https://aihealthindex.io/changelog/braincheck</link>
      <guid isPermaLink="false">aihealthindex.io:change:6a9c312c04c538181acf1b40</guid>
      <pubDate>Thu, 03 Sep 2026 12:00:00 GMT</pubDate>
      <category>Product / capability</category>
      <category>Clinical Decision Support</category>
      <category>Behavioral Health AI</category>
      <category>Remote Monitoring &amp; Chronic Care</category>
      <description><![CDATA[<p>BrainCheck added BrainCheck Screen, a pre screening tool that identifies which patients need fuller cognitive testing. The vendor reports validation on a 99 patient dataset showing 92 percent sensitivity and 74 percent specificity for detecting cognitive impairment.</p><p><strong>Why it matters:</strong> A stated population and both operating characteristics is more than most vendors in this index publish, and it is enough to reason about. Sensitivity of 92 percent with specificity of 74 percent is the right shape for a pre screen, since the job is to avoid missing people and to accept that a quarter of those flagged will test normal. The dataset is small at 99 patients, so the number to ask about is performance in a primary care population rather than a validation cohort.</p><p>Impact: High. Verification: Verified. Type: Product / capability.</p><p>Evidence: <a href="https://braincheck.com/articles/news/braincheck-expands-first-end-to-end-solution-for-cognitive-care">Vendor announcement</a></p><p>Source: <a href="https://aihealthindex.io/changelog/braincheck">AI Health Index change log</a>. Free to reuse with a link back. <a href="https://aihealthindex.io/use-this-data">Terms</a>.</p>]]></description>
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