{ "dataset": { "name": "Healthcare AI Market and FDA Clearance Dataset Sample", "slug": "healthcare-ai-market-fda-dataset", "version": "1.0.0", "release_date": "2026-10-08", "sample_only": true, "full_release_counts": { "devices": 296, "device_classes": 26, "companies": 35, "specialties": 6, "learning_programs": 10, "career_roles": 10, "evidence_topics": 8, "evidence_studies": 192, "total_records": 583 } }, "tables": { "devices": { "columns": [ "k_number", "device_name", "applicant", "state", "country", "decision_date", "decision", "review_panel", "product_code", "device_class_slug", "device_class_title", "specialty_slug", "specialty_label", "vendor_slug", "vendor_group", "source_url", "last_verified" ], "records": [ [ "K260906", "a2z-Abdo-Triage", "A2z Radiology Ai, Inc.", "MA", "US", "2026-09-16", "Substantially Equivalent", "Radiology", "QAS", "radiological-computer-assisted-triage-and-notification-software-qas", "AI Triage and Notification Software for Radiology", "radiology", "Radiology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260906", "2026-10-03" ], [ "K261517", "qCT Lung (v1.0)", "Qure.Ai Technologies Pvt. , Ltd.", "", "IN", "2026-09-14", "Substantially Equivalent", "Radiology", "QDQ", "radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "AI Cancer Detection Software for Radiology", "radiology", "Radiology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K261517", "2026-10-03" ], [ "K260133", "CADDIE", "Odin Medical Limited", "", "GB", "2026-09-12", "Substantially Equivalent", "Gastroenterology, Urology", "QNP", "gastrointesinal-lesion-software-detection-system-qnp", "Gastrointestinal Lesion Detection Software", "gastroenterology-urology", "Gastroenterology, Urology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260133", "2026-10-03" ], [ "K261378", "Rayvolve AZchest", "AZmed", "", "FR", "2026-08-28", "Substantially Equivalent", "Radiology", "QBS", "radiological-computer-assisted-detection-diagnosis-software-for-fracture-qbs", "AI Fracture Detection Software", "radiology", "Radiology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K261378", "2026-10-03" ], [ "K253699", "Tempus ECG-PH", "Tempus AI, Inc.", "IL", "US", "2026-08-21", "Substantially Equivalent", "Cardiovascular", "SAT", "pulmonary-hypertension-machine-learning-based-notification-software-sat", "Pulmonary Hypertension AI Notification", "cardiovascular", "Cardiovascular", "tempus", "life-sciences", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K253699", "2026-10-03" ], [ "K260898", "Transpara (2.1.0)", "Screenpoint Medical B.V.", "", "NL", "2026-08-14", "Substantially Equivalent", "Radiology", "QDQ", "radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "AI Cancer Detection Software for Radiology", "radiology", "Radiology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260898", "2026-10-03" ], [ "K260086", "CadAI-B Dx", "BeamWorks, Inc.", "", "KR", "2026-08-12", "Substantially Equivalent", "Radiology", "QDQ", "radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "AI Cancer Detection Software for Radiology", "radiology", "Radiology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260086", "2026-10-03" ], [ "K260567", "EW10-EC02 Endoscopy Support Program", "Fujifilm Corporation", "", "JP", "2026-08-07", "Substantially Equivalent", "Gastroenterology, Urology", "QNP", "gastrointesinal-lesion-software-detection-system-qnp", "Gastrointestinal Lesion Detection Software", "gastroenterology-urology", "Gastroenterology, Urology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260567", "2026-10-03" ], [ "K252853", "CAD - Lower GI (EC07-01)", "Xiamen Inno Medical Technology Co., Ltd.", "", "CN", "2026-08-05", "Substantially Equivalent", "Gastroenterology, Urology", "QNP", "gastrointesinal-lesion-software-detection-system-qnp", "Gastrointestinal Lesion Detection Software", "gastroenterology-urology", "Gastroenterology, Urology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K252853", "2026-10-03" ], [ "K260303", "See-Mode Augmented Reporting Tool, Breast (SMART-B)", "See-Mode Technologies Pty, Ltd.", "", "AU", "2026-07-28", "Substantially Equivalent", "Radiology", "QDQ", "radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "AI Cancer Detection Software for Radiology", "radiology", "Radiology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260303", "2026-10-03" ], [ "K260338", "ThinkSono Guidance", "ThinkSono GmbH", "", "DE", "2026-07-15", "Substantially Equivalent", "Radiology", "QJU", "image-acquisition-and-or-optimization-guided-by-artificial-intelligence-qju", "AI-Guided Image Acquisition", "radiology", "Radiology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260338", "2026-10-03" ], [ "K261085", "Rapid Vessel Occlusion (Rapid VO)", "iSchemaview", "CO", "US", "2026-07-13", "Substantially Equivalent", "Radiology", "QAS", "radiological-computer-assisted-triage-and-notification-software-qas", "AI Triage and Notification Software for Radiology", "radiology", "Radiology", "rapidai", "imaging-diagnostics", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K261085", "2026-10-03" ], [ "K253751", "CXRDetectAI", "Neurocareai, Inc. (Dba Savelife.Ai)", "TX", "US", "2026-07-08", "Substantially Equivalent", "Radiology", "QFM", "radiological-computer-assisted-prioritization-software-for-lesions-qfm", "AI Lesion Prioritization Software for Radiology", "radiology", "Radiology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K253751", "2026-10-03" ], [ "K253704", "iPredict-DR", "iHealthscreen, Inc.", "NY", "US", "2026-07-02", "Substantially Equivalent", "Ophthalmic", "PIB", "diabetic-retinopathy-detection-device-pib", "Diabetic Retinopathy Detection AI", "ophthalmic", "Ophthalmic", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K253704", "2026-10-03" ], [ "K253884", "Koios DS (3.8)", "Koios Medical, Inc.", "NY", "US", "2026-07-02", "Substantially Equivalent", "Radiology", "POK", "computer-assisted-diagnostic-software-for-lesions-suspicious-for-cancer-pok", "AI Diagnostic Software for Suspicious Lesions", "radiology", "Radiology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K253884", "2026-10-03" ], [ "K260714", "MammoScreen® (5)", "Therapixel", "", "FR", "2026-06-26", "Substantially Equivalent", "Radiology", "QDQ", "radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "AI Cancer Detection Software for Radiology", "radiology", "Radiology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260714", "2026-10-03" ], [ "K260729", "Vascular Assist Occlusion Triage (VAOT) (v1.0)", "GuideAI Health", "MA", "US", "2026-06-18", "Substantially Equivalent", "Radiology", "QAS", "radiological-computer-assisted-triage-and-notification-software-qas", "AI Triage and Notification Software for Radiology", "radiology", "Radiology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260729", "2026-10-03" ], [ "K253825", "Saige-Dx", "DeepHealth, Inc.", "MA", "US", "2026-06-15", "Substantially Equivalent", "Radiology", "QDQ", "radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "AI Cancer Detection Software for Radiology", "radiology", "Radiology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K253825", "2026-10-03" ], [ "K260332", "EchoNext", "Pathwai, Inc.", "NY", "US", "2026-06-08", "Substantially Equivalent", "Cardiovascular", "QXO", "cardiovascular-machine-learning-based-notification-software-qxo", "Cardiovascular Machine Learning Notification Software", "cardiovascular", "Cardiovascular", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260332", "2026-10-03" ], [ "K261519", "Sonio Suspect", "Sonio", "", "FR", "2026-06-04", "Substantially Equivalent", "Radiology", "POK", "computer-assisted-diagnostic-software-for-lesions-suspicious-for-cancer-pok", "AI Diagnostic Software for Suspicious Lesions", "radiology", "Radiology", "", "", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K261519", "2026-10-03" ] ] }, "device_classes": { "columns": [ "slug", "title", "product_code", "specialty_slug", "specialty_label", "fda_device_name", "device_class", "regulation_number", "submission_type", "clearance_count", "first_clearance", "latest_clearance", "definition", "plain_summary", "source_url", "last_verified" ], "records": [ [ "adjunctive-epicardial-vascular-physiologic-status-indicator-qxz", "Adjunctive Coronary Physiology Indicator", "QXZ", "cardiovascular", "Cardiovascular", "Adjunctive Epicardial Vascular Physiologic Status Indicator", "2", "870.2200", "1", 1, "2023-09-08", "2023-09-08", "The adjunctive epicardial vascular physiologic status indicator is a prescription device based on sensor technology or image data to provide information to an interpreting clinician in detecting the possible presence of functionally significant coronary artery disease to suggest the need for further testing. This device is intended for adjunctive use with other clinical workup or patient information and is not intended to quantify the degree to which epicardial disease is limiting flow through a vessel nor is it intended to independently direct therapy.", "Estimates how much a narrowing actually restricts blood flow, from imaging rather than from a wire in the artery.", "https://open.fda.gov/apis/device/510k/", "2026-10-03" ], [ "atrial-fibrillation-risk-prediction-machine-learning-based-notification-software-sbq", "Atrial Fibrillation Risk Prediction AI", "SBQ", "cardiovascular", "Cardiovascular", "Atrial Fibrillation Risk Prediction Machine Learning-Based Notification Software", "2", "870.2380", "1", 1, "2024-06-21", "2024-06-21", "Atrial Fibrillation Risk Prediction machine learning-based notification software employs machine learning techniques to suggest the likelihood of a future occurrence of atrial fibrillation for further referral or diagnostic follow-up.", "Predicts which patients are likely to develop an irregular heartbeat, before it has happened.", "https://open.fda.gov/apis/device/510k/", "2026-10-03" ], [ "cardiac-amyloidosis-machine-learning-based-notification-software-shp", "Cardiac Amyloidosis AI Notification", "SHP", "cardiovascular", "Cardiovascular", "Cardiac Amyloidosis Machine Learning-Based Notification Software", "2", "870.2380", "1", 1, "2026-04-07", "2026-04-07", "Cardiac Amyloidosis machine learning-based notification software employs machine learning techniques to suggest the likelihood of cardiac amyloidosis for further referral or diagnostic follow-up.", "Flags a rare heart disease that is routinely mistaken for ordinary heart failure.", "https://open.fda.gov/apis/device/510k/", "2026-10-03" ], [ "cardiovascular-machine-learning-based-notification-software-qxo", "Cardiovascular Machine Learning Notification Software", "QXO", "cardiovascular", "Cardiovascular", "Cardiovascular Machine Learning-Based Notification Software", "2", "870.2380", "1", 2, "2023-08-03", "2026-06-08", "Cardiovascular machine learning-based notification software employs machine learning techniques to suggest the likelihood of a cardiovascular disease or condition for further referral or diagnostic follow-up. The software identifies a single condition based on one or more non-invasive physiological inputs as part of routine medical care. It is intended as the basis for further testing and is not intended to provide diagnostic quality output. It is not intended to identify or detect arrhythmias.", "Watches heart data for a pattern and sends an alert, without saying what the pattern means.", "https://open.fda.gov/apis/device/510k/", "2026-10-03" ], [ "chest-x-ray-computer-aided-detection-omj", "Chest X-Ray Computer-Aided Detection", "OMJ", "radiology", "Radiology", "Chest X-Ray Computer Aided Detection", "2", "892.2050", "1", 1, "2004-10-08", "2004-10-08", "To assist radiologists in the review of chest radiographic images and highlight potential nodules that the radiologist should review.", "Marks possible findings on a plain chest X-ray.", "https://open.fda.gov/apis/device/510k/", "2026-10-03" ], [ "colon-computed-tomography-system-computer-aided-detection-nwe", "CT Colonography Computer-Aided Detection", "NWE", "radiology", "Radiology", "Colon Computed Tomography System, Computer Aided Detection", "2", "892.2050", "1", 4, "2004-10-08", "2014-12-03", "To assist radiologists in the review of multi-slice computed tomography (msct) exams of the colon and highlight potential polyps that the radiologist should review.", "Flags possible polyps on a CT scan of the colon, as a second read.", "https://open.fda.gov/apis/device/510k/", "2026-10-03" ], [ "computer-assisted-diagnostic-software-for-lesions-suspicious-for-cancer-pok", "AI Diagnostic Software for Suspicious Lesions", "POK", "radiology", "Radiology", "Computer-Assisted Diagnostic Software For Lesions Suspicious For Cancer", "2", "892.2060", "1", 23, "2017-07-19", "2026-07-02", "Assist users in characterizing lesions identified on acquired medical images", "Helps characterize a lesion that has already been found, rather than finding it in the first place.", "https://open.fda.gov/apis/device/510k/", "2026-10-03" ], [ "coronary-artery-disease-machine-learning-based-notification-software-qxx", "Coronary Artery Disease AI Notification", "QXX", "cardiovascular", "Cardiovascular", "Coronary Artery Disease Machine Learning-Based Notification Software", "2", "870.2380", "1", 1, "2023-09-08", "2023-09-08", "Coronary Artery Disease machine learning-based notification software employs machine learning techniques to suggest the likelihood of coronary artery disease for further referral or diagnostic follow-up.", "Flags patients whose data suggests narrowed heart arteries, for a clinician to follow up.", "https://open.fda.gov/apis/device/510k/", "2026-10-03" ], [ "diabetic-retinopathy-detection-device-pib", "Diabetic Retinopathy Detection AI", "PIB", "ophthalmic", "Ophthalmic", "Diabetic Retinopathy Detection Device", "2", "886.1100", "1", 8, "2018-04-11", "2026-07-02", "A retinal diagnostic software device is a prescription software device that incorporates an adaptive algorithm to evaluate ophthalmic images for diagnostic screening to identify retinal diseases or conditions.", "Screens photographs of the back of the eye for diabetic damage, in some cases giving the result without a specialist reading it.", "https://open.fda.gov/apis/device/510k/", "2026-10-03" ], [ "digital-cervical-cytology-slide-imaging-system-with-artificial-intelligence-algorithm-qyv", "AI Cervical Cytology Slide Imaging", "QYV", "pathology", "Pathology", "Digital Cervical Cytology Slide Imaging System With Artificial Intelligence Algorithm", "2", "864.3900", "1", 1, "2024-01-31", "2024-01-31", "The digital cervical cytology slide imaging system with artificial intelligence (AI) algorithm is a prescription in vitro diagnostic device consisting of an automated digital slide creation, viewing, and management system intended to aid in the review of digital images of slides prepared from Pap test specimens and conventional Pap smears by selecting and presenting areas of interest to facilitate interpretation by the reader. The AI software algorithm uses machine learning techniques to provide information to the user about the presence, location, or characteristics of areas of the image with clinical implications. Information from this device is intended to assist the user in rendering a cytology diagnosis.", "Scans cervical screening slides and uses AI to pick out the areas a human should review.", "https://open.fda.gov/apis/device/510k/", "2026-10-03" ] ] }, "companies": { "columns": [ "slug", "name", "category", "company_structure", "market_access", "public_market_access", "issuer_name", "ticker", "exchange", "relationship_to_security", "official_url", "profile_url", "careers_url", "investor_relations_url", "last_verified" ], "records": [ [ "ge-healthcare", "GE HealthCare", "imaging-diagnostics", "Public company", "direct", "Direct listing: Nasdaq: GEHC.", "GE HealthCare Technologies Inc.", "GEHC", "Nasdaq", "direct listing", "https://www.gehealthcare.com/", "https://www.aihealthcarenow.com/library/healthcare-ai-companies/imaging-diagnostics/ge-healthcare/", "https://careers.gehealthcare.com/", "https://investor.gehealthcare.com/", "2026-09-28" ], [ "lunit", "Lunit", "imaging-diagnostics", "Public company", "direct", "Direct listing: Korea Exchange KOSDAQ: 328130.", "Lunit Inc.", "328130", "KOSDAQ", "direct listing", "https://www.lunit.io/", "https://www.aihealthcarenow.com/library/healthcare-ai-companies/imaging-diagnostics/lunit/", "https://www.lunit.io/en/careers/", "https://www.lunit.io/en/investors/", "2026-09-28" ], [ "philips", "Philips", "imaging-diagnostics", "Public company", "direct", "Direct listings: NYSE: PHG and Euronext Amsterdam: PHIA.", "Koninklijke Philips N.V.", "PHG / PHIA", "NYSE / Euronext Amsterdam", "direct listing", "https://www.philips.com/healthcare", "https://www.aihealthcarenow.com/library/healthcare-ai-companies/imaging-diagnostics/philips/", "https://www.careers.philips.com/", "https://www.philips.com/a-w/about/investor-relations.html", "2026-09-28" ], [ "recursion", "Recursion", "life-sciences", "Public company", "direct", "Direct listing: Nasdaq: RXRX.", "Recursion Pharmaceuticals, Inc.", "RXRX", "Nasdaq", "direct listing", "https://www.recursion.com/", "https://www.aihealthcarenow.com/library/healthcare-ai-companies/life-sciences/recursion/", "https://www.recursion.com/careers", "https://ir.recursion.com/", "2026-09-28" ], [ "siemens-healthineers", "Siemens Healthineers", "imaging-diagnostics", "Public company", "direct", "Direct listing: Frankfurt and Xetra: SHL.", "Siemens Healthineers AG", "SHL", "Frankfurt and Xetra", "direct listing", "https://www.siemens-healthineers.com/", "https://www.aihealthcarenow.com/library/healthcare-ai-companies/imaging-diagnostics/siemens-healthineers/", "https://www.siemens-healthineers.com/careers", "https://www.siemens-healthineers.com/investor-relations", "2026-09-28" ], [ "tempus", "Tempus", "life-sciences", "Public company", "direct", "Direct listing: Nasdaq: TEM.", "Tempus AI, Inc.", "TEM", "Nasdaq", "direct listing", "https://www.tempus.com/", "https://www.aihealthcarenow.com/library/healthcare-ai-companies/life-sciences/tempus/", "https://www.tempus.com/careers/", "https://investors.tempus.com/", "2026-09-28" ], [ "deephealth", "DeepHealth", "imaging-diagnostics", "Wholly owned subsidiary of RadNet", "parent", "Public parent: RadNet, Nasdaq: RDNT.", "RadNet, Inc.", "RDNT", "Nasdaq", "public parent", "https://deephealth.com/", "https://www.aihealthcarenow.com/library/healthcare-ai-companies/imaging-diagnostics/deephealth/", "https://deephealth.com/careers/", "https://investor.radnet.com/", "2026-09-28" ], [ "isomorphic-labs", "Isomorphic Labs", "life-sciences", "Alphabet company", "parent", "Public parent: Alphabet, Nasdaq: GOOGL and GOOG.", "Alphabet Inc.", "GOOGL / GOOG", "Nasdaq", "public parent", "https://www.isomorphiclabs.com/", "https://www.aihealthcarenow.com/library/healthcare-ai-companies/life-sciences/isomorphic-labs/", "https://www.isomorphiclabs.com/careers", "", "2026-09-28" ], [ "nuance-dax", "Microsoft Nuance (DAX / Dragon Copilot)", "ambient-documentation", "Microsoft healthcare product line", "parent", "Public parent: Microsoft, Nasdaq: MSFT.", "Microsoft Corporation", "MSFT", "Nasdaq", "public parent", "https://www.nuance.com/healthcare.html", "https://www.aihealthcarenow.com/library/healthcare-ai-companies/ambient-documentation/nuance-dax/", "https://careers.microsoft.com/", "https://www.microsoft.com/en-us/Investor/", "2026-09-28" ], [ "abridge", "Abridge", "ambient-documentation", "Private company", "private", "No direct public shares are available.", "", "", "", "none", "https://www.abridge.com/", "https://www.aihealthcarenow.com/library/healthcare-ai-companies/ambient-documentation/abridge/", "https://www.abridge.com/careers", "", "2026-09-28" ] ] }, "specialties": { "columns": [ "slug", "title", "review_panel", "class_count", "clearance_count", "class_slugs", "description", "last_verified" ], "records": [ [ "cardiovascular", "Cardiovascular", "Cardiovascular", 8, 15, "cardiovascular-machine-learning-based-notification-software-qxo | coronary-artery-disease-machine-learning-based-notification-software-qxx | adjunctive-epicardial-vascular-physiologic-status-indicator-qxz | reduced-ejection-fraction-machine-learning-based-notification-software-qye | pulmonary-hypertension-machine-learning-based-notification-software-sat | atrial-fibrillation-risk-prediction-machine-learning-based-notification-software-sbq | hypertension-machine-learning-based-notification-software-sfr | cardiac-amyloidosis-machine-learning-based-notification-software-shp", "Heart and vessel AI that watches for one named condition and raises a hand. Each product here is cleared for one specific warning.", "2026-10-03" ], [ "gastroenterology-urology", "Gastroenterology, Urology", "Gastroenterology, Urology", 1, 23, "gastrointesinal-lesion-software-detection-system-qnp", "Colonoscopy software that flags possible lesions live, while the scope is still moving.", "2026-10-03" ], [ "neurology", "Neurology", "Neurology", 1, 6, "pediatric-autism-spectrum-disorder-diagnosis-aid-qpf", "A short list, led by software cleared to help diagnose autism in young children.", "2026-10-03" ], [ "ophthalmic", "Ophthalmic", "Ophthalmic", 1, 8, "diabetic-retinopathy-detection-device-pib", "Eye screening AI, including the first products cleared to give a result without a specialist reading the image.", "2026-10-03" ], [ "pathology", "Pathology", "Pathology", 4, 5, "software-algorithm-device-to-assist-users-in-digital-pathology-qpn | digital-cervical-cytology-slide-imaging-system-with-artificial-intelligence-algorithm-qyv | pathology-software-algorithm-device-analyzing-digital-images-for-prostate-cancer-prognosis-sfh | pathology-software-algorithm-device-analyzing-digital-images-for-breast-cancer-prognosis-shw", "Software that reads digitized slides. Small in number, and the first products cleared to help predict how a cancer will behave.", "2026-10-03" ], [ "radiology", "Radiology", "Radiology", 10, 238, "colon-computed-tomography-system-computer-aided-detection-nwe | lung-computed-tomography-system-computer-aided-detection-oeb | chest-x-ray-computer-aided-detection-omj | computer-assisted-diagnostic-software-for-lesions-suspicious-for-cancer-pok | radiological-computer-assisted-triage-and-notification-software-qas | radiological-computer-assisted-detection-diagnosis-software-for-fracture-qbs | radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq | radiological-computer-assisted-prioritization-software-for-lesions-qfm | image-acquisition-and-or-optimization-guided-by-artificial-intelligence-qju | radiological-machine-learning-based-quantitative-imaging-software-with-change-control-plan-qvd", "Most cleared healthcare AI reads pictures. This is where the scans live, and it is by far the busiest field on the list.", "2026-10-03" ] ] }, "learning_programs": { "columns": [ "slug", "title", "provider", "credential", "who_it_suits", "description", "url", "link_status", "link_checked", "last_verified" ], "records": [ [ "abpm-clinical-informatics", "Clinical Informatics subspecialty board certification", "American Board of Preventive Medicine", "Board certification, physicians only", "Physicians who want the formal credential behind a chief medical information officer role.", "This is the heavyweight credential in the field and the only one on this page that is a medical board certification. Eligibility rules are strict and have changed over time, so read the current requirements rather than a summary.", "https://www.theabpm.org/become-certified/subspecialties/clinical-informatics/", "ok", "2026-10-03", "2026-09-28" ], [ "acr-data-science-institute", "Data Science Institute resources and AI certification work", "American College of Radiology", "Professional body program", "Radiologists and imaging informatics staff evaluating or deploying imaging AI.", "Radiology holds most of the cleared AI in US healthcare, and this is the professional body doing the practical work on how to evaluate and monitor it.", "https://www.acrdsi.org/", "ok", "2026-10-03", "2026-09-28" ], [ "ahima-health-information", "Health information and data credentials", "American Health Information Management Association", "Professional certification", "Health information management, coding and clinical documentation staff.", "The credential family that matters most if your work sits on the documentation and data governance side rather than the modeling side. Directly relevant to the roles most changed by ambient AI.", "https://www.ahima.org/", "ok", "2026-10-03", "2026-09-28" ], [ "amia-10x10", "10x10 informatics courses", "American Medical Informatics Association", "Professional course, university partnered", "Working clinicians and informatics staff building toward the board or toward an informatics role.", "Long running and well regarded inside the field. Often used as preparation for the clinical informatics board rather than as a standalone credential.", "https://amia.org/education-events/10x10-courses", "blocked", "2026-10-03", "2026-09-28" ], [ "coursera-ai-for-medicine", "AI for Medicine Specialization", "DeepLearning.AI, delivered on Coursera", "Technical course, certificate of completion", "People who can already code and want the medical application, not the other way round.", "Hands on with medical imaging and clinical prediction. Expect to write Python rather than read about it.", "https://www.coursera.org/specializations/ai-for-medicine", "ok", "2026-10-03", "2026-09-28" ] ] }, "career_roles": { "columns": [ "slug", "title", "one_line", "employer_side", "remote_reality", "what_you_do", "background", "skills", "ai_exposure", "canonical_url", "last_verified" ], "records": [ [ "ai-governance-lead", "Healthcare AI Governance Lead", "Writes the rules for how a hospital adopts, monitors and retires AI, and makes them stick.", "Hospital or health system", "Often hybrid. Policy work travels; the committee meetings and the awkward conversations do not.", [ "A few years ago this was a committee nobody wanted to sit on. Now it is a named job, because boards started asking who signed off.", "The work is building the process: how a tool gets proposed, what evidence it needs, who approves it, what gets monitored after it is live, and what triggers switching it off. Then keeping an inventory, because most hospitals genuinely do not know how many models are running inside their systems.", "The hard part is not writing the policy. It is that the policy has to be light enough that clinicians follow it and firm enough that it catches a bad purchase." ], "Compliance, clinical informatics, quality and safety, or risk. Increasingly a lateral move from privacy work.", "Turning a framework into a process people actually use | Keeping a live inventory of deployed models | Post-deployment monitoring and the authority to pause something | Knowing which state and federal rules apply and when they changed", "Growing fast. This role barely existed five years ago and now appears on organization charts.", "/careers/ai-governance-lead/", "2026-09-28" ], [ "clinical-ai-lead", "Clinical AI Lead", "Decides which AI a hospital actually buys, and owns the answer when someone asks whether it works here.", "Hospital or health system", "Rarely remote. The job runs on hallway trust with clinicians, and that does not survive being a name on a screen.", [ "This is the person in the middle. Vendors pitch them, clinicians complain to them, and the finance team asks them for a number.", "The daily work is less technical than the title suggests. It is reading an evidence pack and spotting that the study was done on a different scanner. It is asking what happens to the cases the software does not flag. It is telling a department head that the tool they want is cleared to move a scan up the queue and not cleared to say what is on it.", "The reason the role exists at all is that buying clinical software badly is expensive and slow to notice. Somebody has to be accountable before go-live rather than after." ], "Usually a clinician who got interested in the systems side, often through informatics. Sometimes a biomedical engineer who got interested in the clinical side. Almost never someone who came straight from software.", "Reading a clinical study well enough to find the weak assumption | Knowing what a regulatory clearance does and does not cover | Running a local validation on your own patients before go-live | Saying no to an executive who already told the board yes", "Growing, not shrinking. Every tool a hospital adds needs someone accountable for it, so more AI means more of this job, not less.", "/careers/clinical-ai-lead/", "2026-09-28" ], [ "clinical-documentation-specialist", "Clinical Documentation Specialist", "The role most directly changed by ambient AI, and the clearest test of whether these tools move work or remove it.", "Hospital or health system", "Increasingly remote, and it was already heading that way before ambient AI arrived.", [ "This role reviews and improves the clinical record so it reflects what actually happened and supports the right coding.", "Ambient AI landed directly on top of it. The software drafts the note, which changes the job from producing documentation to checking documentation, and those are genuinely different skills.", "Worth being honest about the direction here. This is the role on this page where the tools are closest to the work, and the people doing well in it have moved toward the review, quality and audit side rather than the production side." ], "Nursing, coding, or health information management, usually with a credential.", "Reviewing an AI-drafted note for what it quietly left out | Coding and compliance, which the software does not own | Measuring how much of a draft actually gets edited | Auditing quality once volume goes up", "The highest on this page. The work is shifting from writing to checking, and the checking part is growing.", "/careers/clinical-documentation-specialist/", "2026-09-28" ], [ "clinical-evidence-lead", "Clinical Evidence Lead", "Builds the proof that a product works, so buyers have something to read that is not a brochure.", "Vendor", "Often remote, with travel to the sites running the studies.", [ "Every buyer on this site is told to ask for published evidence. Somebody has to go and create it.", "The work is designing studies with real hospitals, getting them run, getting them published, and then translating them for the sales team without overstating what was found. The tension in the job is permanent: the company wants a strong claim and the data supports a narrower one.", "The teams that do this well end up with something competitors cannot copy quickly, because a trial takes years." ], "Clinical research, medical affairs, or academia. Frequently a former researcher who wanted the work to ship.", "Study design that answers a buyer question, not just a scientific one | Working with health system research offices and their timelines | Publishing, including handling reviewers who dislike industry studies | Holding the line on what the data actually shows", "Low. The bottleneck is access to sites and patients, not writing.", "/careers/clinical-evidence-lead/", "2026-09-28" ], [ "clinical-implementation-manager", "Clinical Implementation Manager", "Takes a signed contract and turns it into a tool people actually use six months later.", "Vendor", "Usually remote with heavy travel. The go-live weeks are on site.", [ "The gap between bought and used is where most healthcare software dies, and this role lives in that gap.", "The work is scheduling, training, integration chasing, and managing the department that agreed to the project without reading it. The technical part is the smallest part. Most of it is persuading busy clinicians to change something that already works well enough for them.", "People who are good at this are unusually valuable and unusually hard to hire, because the skill is a mix of clinical credibility and stubbornness." ], "Nursing, technologist, or clinic operations, then a move to the vendor side. Occasionally project management with enough healthcare exposure to be taken seriously.", "Running a go-live without losing the department | Training clinicians who did not ask for the tool | Spotting the workflow problem behind the reported software problem | Measuring adoption after the launch excitement fades", "Low. This is the human half of the deployment and it does not automate.", "/careers/clinical-implementation-manager/", "2026-09-28" ] ] }, "evidence_topics": { "columns": [ "slug", "title", "linked_group", "query", "total_indexed", "study_count", "oldest_year", "newest_year", "design_mix", "description", "source_url", "last_verified" ], "records": [ [ "ambient-ai-documentation", "Ambient AI Documentation", "ambient-documentation", "(TITLE:\"ambient\" OR TITLE:\"scribe\" OR TITLE:\"scribes\") AND (TITLE_ABS:\"documentation\" OR TITLE_ABS:\"scribe\" OR TITLE_ABS:\"burnout\") AND (TITLE_ABS:\"artificial intelligence\" OR TITLE_ABS:\"AI\" OR TITLE_ABS:\"large language model\")", 268, 24, "2018", "2025", "16 | 3 | 2 | 1 | 1 | 1", "Software that listens to the visit and drafts the note. The most widely bought healthcare AI right now, and the one with the fastest growing research base.", "https://europepmc.org/", "2026-10-03" ], [ "breast-cancer-detection", "AI in Breast Cancer Screening", "imaging-diagnostics", "(TITLE:\"mammography\" OR TITLE:\"breast cancer screening\" OR TITLE:\"mammograms\") AND (TITLE_ABS:\"artificial intelligence\" OR TITLE_ABS:\"deep learning\" OR TITLE_ABS:\"computer-aided detection\")", 1071, 24, "2000", "2023", "21 | 2 | 1", "Screening mammography AI, the oldest research base in the field and the one with the largest prospective trials.", "https://europepmc.org/", "2026-10-03" ], [ "colonoscopy-polyp-detection", "AI Polyp Detection in Colonoscopy", "", "(TITLE:\"colonoscopy\" OR TITLE:\"colonoscopies\" OR TITLE:\"adenoma detection\" OR TITLE:\"polyp\" OR TITLE:\"polyps\") AND (TITLE_ABS:\"artificial intelligence\" OR TITLE_ABS:\"computer-aided detection\" OR TITLE_ABS:\"deep learning\")", 1012, 24, "2016", "2025", "13 | 7 | 3 | 1", "Software that highlights possible polyps on the live scope view. One of the few areas with a solid stack of randomized trials.", "https://europepmc.org/", "2026-10-03" ], [ "diabetic-retinopathy-screening", "Autonomous Diabetic Retinopathy Screening", "", "(TITLE:\"diabetic retinopathy\") AND (TITLE_ABS:\"screening\" OR TITLE_ABS:\"autonomous\" OR TITLE_ABS:\"point-of-care\") AND (TITLE_ABS:\"artificial intelligence\" OR TITLE_ABS:\"deep learning\" OR TITLE_ABS:\"automated\")", 728, 24, "2013", "2022", "19 | 5", "Eye screening software, including systems cleared to give a result without a specialist reading the image. The deepest evidence base in autonomous AI.", "https://europepmc.org/", "2026-10-03" ], [ "healthcare-ai-roi", "Cost and Return on Healthcare AI", "", "(TITLE:\"cost effectiveness\" OR TITLE:\"cost-effectiveness\" OR TITLE:\"economic evaluation\" OR TITLE:\"return on investment\" OR TITLE:\"cost savings\" OR TITLE:\"budget impact\" OR TITLE:\"cost analysis\") AND (TITLE:\"artificial intelligence\" OR TITLE:\"deep learning\" OR TITLE:\"machine learning\" OR TITLE:\"AI\" OR TITLE:\"AI-aided\" OR TITLE:\"automated\" OR TITLE:\"algorithm\")", 381, 24, "1998", "2025", "20 | 2 | 1 | 1", "Published cost-effectiveness and economic evaluations of healthcare AI. A short list, which is itself the finding.", "https://europepmc.org/", "2026-10-03" ] ] }, "evidence_studies": { "columns": [ "topic_slug", "topic_title", "study_title", "authors", "journal", "year", "design", "pmid", "doi", "cited_by", "open_access", "url" ], "records": [ [ "ambient-ai-documentation", "Ambient AI Documentation", "Ambient artificial intelligence scribes: physician burnout and perspectives on usability and documentation burden.", "Shah SJ and 13 others", "Journal of the American Medical Informatics Association : JAMIA", "2025", "Study", "39657021", "10.1093/jamia/ocae295", 142, false, "https://europepmc.org/article/MED/39657021" ], [ "ambient-ai-documentation", "Ambient AI Documentation", "Clinician Experiences With Ambient Scribe Technology to Assist With Documentation Burden and Efficiency.", "Duggan MJ and 6 others", "JAMA network open", "2025", "Study", "39969880", "10.1001/jamanetworkopen.2024.60637", 133, true, "https://europepmc.org/article/MED/39969880" ], [ "ambient-ai-documentation", "Ambient AI Documentation", "Use of Ambient AI Scribes to Reduce Administrative Burden and Professional Burnout.", "Olson KD and 10 others", "JAMA network open", "2025", "Study", "41037268", "10.1001/jamanetworkopen.2025.34976", 131, true, "https://europepmc.org/article/MED/41037268" ], [ "ambient-ai-documentation", "Ambient AI Documentation", "Ambient artificial intelligence scribes: utilization and impact on documentation time.", "Ma SP and 13 others", "Journal of the American Medical Informatics Association : JAMIA", "2025", "Study", "39688515", "10.1093/jamia/ocae304", 124, false, "https://europepmc.org/article/MED/39688515" ], [ "ambient-ai-documentation", "Ambient AI Documentation", "Physician Perspectives on Ambient AI Scribes.", "Shah SJ and 14 others", "JAMA network open", "2025", "Study", "40126477", "10.1001/jamanetworkopen.2025.1904", 111, true, "https://europepmc.org/article/MED/40126477" ], [ "ambient-ai-documentation", "Ambient AI Documentation", "The impact of nuance DAX ambient listening AI documentation: a cohort study.", "Haberle T and 8 others", "Journal of the American Medical Informatics Association : JAMIA", "2024", "Cohort study", "38345343", "10.1093/jamia/ocae022", 111, false, "https://europepmc.org/article/MED/38345343" ], [ "ambient-ai-documentation", "Ambient AI Documentation", "Evaluation of an Ambient Artificial Intelligence Documentation Platform for Clinicians.", "Stults CD and 8 others", "JAMA network open", "2025", "Study", "40314951", "10.1001/jamanetworkopen.2025.8614", 105, true, "https://europepmc.org/article/MED/40314951" ], [ "ambient-ai-documentation", "Ambient AI Documentation", "Challenges of developing a digital scribe to reduce clinical documentation burden.", "Quiroz JC and 5 others", "NPJ digital medicine", "2019", "Review", "31799422", "10.1038/s41746-019-0190-1", 98, true, "https://europepmc.org/article/MED/31799422" ], [ "ambient-ai-documentation", "Ambient AI Documentation", "The digital scribe.", "Coiera E and 3 others", "NPJ digital medicine", "2018", "Review", "31304337", "10.1038/s41746-018-0066-9", 92, true, "https://europepmc.org/article/MED/31304337" ], [ "ambient-ai-documentation", "Ambient AI Documentation", "Enhancing clinical documentation with ambient artificial intelligence: a quality improvement survey assessing clinician perspectives on work burden, burnout, and job satisfaction.", "Albrecht M and 8 others", "JAMIA open", "2025", "Survey", "39991073", "10.1093/jamiaopen/ooaf013", 78, true, "https://europepmc.org/article/MED/39991073" ], [ "ambient-ai-documentation", "Ambient AI Documentation", "Use of an ambient artificial intelligence tool to improve quality of clinical documentation.", "Balloch J and 11 others", "Future healthcare journal", "2024", "Study", "39371531", "10.1016/j.fhj.2024.100157", 77, true, "https://europepmc.org/article/MED/39371531" ], [ "ambient-ai-documentation", "Ambient AI Documentation", "Ambient AI Scribes in Clinical Practice: A Randomized Trial.", "Lukac PJ and 8 others", "NEJM AI", "2025", "Randomized trial", "41497288", "10.1056/aioa2501000", 64, false, "https://europepmc.org/article/MED/41497288" ], [ "ambient-ai-documentation", "Ambient AI Documentation", "Artificial Intelligence Scribe and Large Language Model Technology in Healthcare Documentation: Advantages, Limitations, and Recommendations.", "Mess SA and 2 others", "Plastic and reconstructive surgery. Global open", "2025", "Study", "39823022", "10.1097/gox.0000000000006450", 62, true, "https://europepmc.org/article/MED/39823022" ], [ "ambient-ai-documentation", "Ambient AI Documentation", "The Impact of AI Scribes on Streamlining Clinical Documentation: A Systematic Review.", "Sasseville M and 11 others", "Healthcare (Basel, Switzerland)", "2025", "Systematic review", "40565474", "10.3390/healthcare13121447", 56, true, "https://europepmc.org/article/MED/40565474" ], [ "ambient-ai-documentation", "Ambient AI Documentation", "The association between use of ambient voice technology documentation during primary care patient encounters, documentation burden, and provider burnout.", "Owens LM and 4 others", "Family practice", "2024", "Study", "37672297", "10.1093/fampra/cmad092", 54, false, "https://europepmc.org/article/MED/37672297" ] ] } }, "codebook": { "dataset": "healthcare-ai-market-fda-dataset", "version": "1.0.0", "release_date": "2026-10-08", "tables": { "devices": { "columns": [ "k_number", "device_name", "applicant", "state", "country", "decision_date", "decision", "review_panel", "product_code", "device_class_slug", "device_class_title", "specialty_slug", "specialty_label", "vendor_slug", "vendor_group", "source_url", "last_verified" ], "record_count": 296 }, "device_classes": { "columns": [ "slug", "title", "product_code", "specialty_slug", "specialty_label", "fda_device_name", "device_class", "regulation_number", "submission_type", "clearance_count", "first_clearance", "latest_clearance", "definition", "plain_summary", "source_url", "last_verified" ], "record_count": 26 }, "companies": { "columns": [ "slug", "name", "category", "company_structure", "market_access", "public_market_access", "issuer_name", "ticker", "exchange", "relationship_to_security", "official_url", "profile_url", "careers_url", "investor_relations_url", "last_verified" ], "record_count": 35 }, "specialties": { "columns": [ "slug", "title", "review_panel", "class_count", "clearance_count", "class_slugs", "description", "last_verified" ], "record_count": 6 }, "learning_programs": { "columns": [ "slug", "title", "provider", "credential", "who_it_suits", "description", "url", "link_status", "link_checked", "last_verified" ], "record_count": 10 }, "career_roles": { "columns": [ "slug", "title", "one_line", "employer_side", "remote_reality", "what_you_do", "background", "skills", "ai_exposure", "canonical_url", "last_verified" ], "record_count": 10 }, "evidence_topics": { "columns": [ "slug", "title", "linked_group", "query", "total_indexed", "study_count", "oldest_year", "newest_year", "design_mix", "description", "source_url", "last_verified" ], "record_count": 8 }, "evidence_studies": { "columns": [ "topic_slug", "topic_title", "study_title", "authors", "journal", "year", "design", "pmid", "doi", "cited_by", "open_access", "url" ], "record_count": 192 } }, "boundaries": [ "No patient records, protected health information, claims, diagnoses, treatment outcomes, or clinical predictions.", "Evidence abstracts are excluded from the commercial package. Bibliographic facts and source links are retained.", "Market prices, market capitalization, and other time-sensitive quote data are excluded. Company and security relationships are factual reference fields.", "FDA clearance records describe regulatory decisions and do not establish clinical performance, safety for a specific patient, or investment merit." ], "source_notes": [ "FDA device records trace to openFDA and FDA 510(k) public records.", "Evidence citations trace to Europe PMC records through source URLs.", "Company, program, career, and specialty records are curated by AI Healthcare Now and carry verification dates." ] } }