{ "dataset": { "name": "Healthcare AI Market and FDA Clearance Dataset Sample", "slug": "healthcare-ai-market-fda-dataset", "version": "1.1.0", "release_date": "2026-10-08", "sample_only": true, "full_release_counts": { "devices": 295, "manufacturers": 126, "relationships": 295, "research_relationships": 192, "device_classes": 25, "companies": 35, "specialties": 6, "learning_programs": 10, "career_roles": 10, "evidence_topics": 8, "evidence_studies": 189, "entity_records": 704, "relationship_records": 487, "total_records": 1191 }, "quality_summary": { "stable_entity_ids": 704, "explicit_relationship_rows": 487, "device_relationship_rows": 295, "research_topic_relationship_rows": 192, "normalized_manufacturer_identities": 126, "devices_linked_to_curated_companies": 68, "devices_with_normalized_applicant_only": 227, "device_company_link_rate": "0.2305", "device_records_with_source_url": 295, "device_records_with_verification_date": 295, "source_device_class_records": 26, "canonical_device_classes": 25, "collapsed_device_class_aliases": 1 } }, "tables": { "devices": { "record_type": "entity", "columns": [ "record_id", "k_number", "device_name", "applicant", "applicant_id", "applicant_slug", "state", "country", "decision_date", "decision_year", "clearance_recency_band", "decision", "review_panel", "relationship_count", "product_codes", "device_class_ids", "device_class_slugs", "device_class_titles", "specialty_ids", "specialty_slugs", "specialty_labels", "company_id", "company_slug", "company_name", "company_link_status", "company_match_method", "vendor_group", "source_type", "source_url", "provenance_status", "quality_flags", "last_verified" ], "records": [ [ "fda-510k:K260906", "K260906", "a2z-Abdo-Triage", "A2z Radiology Ai, Inc.", "manufacturer:a2z-radiology-ai-inc", "a2z-radiology-ai-inc", "MA", "US", "2026-09-16", 2026, "last_24_months", "Substantially Equivalent", "Radiology", 1, "QAS", "device-class:radiological-computer-assisted-triage-and-notification-software-qas", "radiological-computer-assisted-triage-and-notification-software-qas", "AI Triage and Notification Software for Radiology", "specialty:radiology", "radiology", "Radiology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260906", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K261517", "K261517", "qCT Lung (v1.0)", "Qure.Ai Technologies Pvt. , Ltd.", "manufacturer:qure-ai-technologies-pvt-ltd", "qure-ai-technologies-pvt-ltd", "", "IN", "2026-09-14", 2026, "last_24_months", "Substantially Equivalent", "Radiology", 1, "QDQ", "device-class:radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "AI Cancer Detection Software for Radiology", "specialty:radiology", "radiology", "Radiology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K261517", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K260133", "K260133", "CADDIE", "Odin Medical Limited", "manufacturer:odin-medical-limited", "odin-medical-limited", "", "GB", "2026-09-12", 2026, "last_24_months", "Substantially Equivalent", "Gastroenterology, Urology", 1, "QNP", "device-class:gastrointesinal-lesion-software-detection-system-qnp", "gastrointesinal-lesion-software-detection-system-qnp", "Gastrointestinal Lesion Detection Software", "specialty:gastroenterology-urology", "gastroenterology-urology", "Gastroenterology, Urology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260133", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K261378", "K261378", "Rayvolve AZchest", "AZmed", "manufacturer:azmed", "azmed", "", "FR", "2026-08-28", 2026, "last_24_months", "Substantially Equivalent", "Radiology", 1, "QBS", "device-class:radiological-computer-assisted-detection-diagnosis-software-for-fracture-qbs", "radiological-computer-assisted-detection-diagnosis-software-for-fracture-qbs", "AI Fracture Detection Software", "specialty:radiology", "radiology", "Radiology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K261378", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K253699", "K253699", "Tempus ECG-PH", "Tempus AI, Inc.", "manufacturer:tempus-ai-inc", "tempus-ai-inc", "IL", "US", "2026-08-21", 2026, "last_24_months", "Substantially Equivalent", "Cardiovascular", 1, "SAT", "device-class:pulmonary-hypertension-machine-learning-based-notification-software-sat", "pulmonary-hypertension-machine-learning-based-notification-software-sat", "Pulmonary Hypertension AI Notification", "specialty:cardiovascular", "cardiovascular", "Cardiovascular", "company:tempus", "tempus", "Tempus", "linked_curated_company", "source_vendor_slug", "life-sciences", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K253699", "source_link_and_verification_date", "none", "2026-10-03" ], [ "fda-510k:K260898", "K260898", "Transpara (2.1.0)", "Screenpoint Medical B.V.", "manufacturer:screenpoint-medical-b-v", "screenpoint-medical-b-v", "", "NL", "2026-08-14", 2026, "last_24_months", "Substantially Equivalent", "Radiology", 1, "QDQ", "device-class:radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "AI Cancer Detection Software for Radiology", "specialty:radiology", "radiology", "Radiology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260898", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K260086", "K260086", "CadAI-B Dx", "BeamWorks, Inc.", "manufacturer:beamworks-inc", "beamworks-inc", "", "KR", "2026-08-12", 2026, "last_24_months", "Substantially Equivalent", "Radiology", 1, "QDQ", "device-class:radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "AI Cancer Detection Software for Radiology", "specialty:radiology", "radiology", "Radiology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260086", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K260567", "K260567", "EW10-EC02 Endoscopy Support Program", "Fujifilm Corporation", "manufacturer:fujifilm-corporation", "fujifilm-corporation", "", "JP", "2026-08-07", 2026, "last_24_months", "Substantially Equivalent", "Gastroenterology, Urology", 1, "QNP", "device-class:gastrointesinal-lesion-software-detection-system-qnp", "gastrointesinal-lesion-software-detection-system-qnp", "Gastrointestinal Lesion Detection Software", "specialty:gastroenterology-urology", "gastroenterology-urology", "Gastroenterology, Urology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260567", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K252853", "K252853", "CAD - Lower GI (EC07-01)", "Xiamen Inno Medical Technology Co., Ltd.", "manufacturer:xiamen-inno-medical-technology-co-ltd", "xiamen-inno-medical-technology-co-ltd", "", "CN", "2026-08-05", 2026, "last_24_months", "Substantially Equivalent", "Gastroenterology, Urology", 1, "QNP", "device-class:gastrointesinal-lesion-software-detection-system-qnp", "gastrointesinal-lesion-software-detection-system-qnp", "Gastrointestinal Lesion Detection Software", "specialty:gastroenterology-urology", "gastroenterology-urology", "Gastroenterology, Urology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K252853", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K260303", "K260303", "See-Mode Augmented Reporting Tool, Breast (SMART-B)", "See-Mode Technologies Pty, Ltd.", "manufacturer:see-mode-technologies-pty-ltd", "see-mode-technologies-pty-ltd", "", "AU", "2026-07-28", 2026, "last_24_months", "Substantially Equivalent", "Radiology", 1, "QDQ", "device-class:radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "AI Cancer Detection Software for Radiology", "specialty:radiology", "radiology", "Radiology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260303", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K260338", "K260338", "ThinkSono Guidance", "ThinkSono GmbH", "manufacturer:thinksono-gmbh", "thinksono-gmbh", "", "DE", "2026-07-15", 2026, "last_24_months", "Substantially Equivalent", "Radiology", 1, "QJU", "device-class:image-acquisition-and-or-optimization-guided-by-artificial-intelligence-qju", "image-acquisition-and-or-optimization-guided-by-artificial-intelligence-qju", "AI-Guided Image Acquisition", "specialty:radiology", "radiology", "Radiology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260338", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K261085", "K261085", "Rapid Vessel Occlusion (Rapid VO)", "iSchemaview", "manufacturer:ischemaview", "ischemaview", "CO", "US", "2026-07-13", 2026, "last_24_months", "Substantially Equivalent", "Radiology", 1, "QAS", "device-class:radiological-computer-assisted-triage-and-notification-software-qas", "radiological-computer-assisted-triage-and-notification-software-qas", "AI Triage and Notification Software for Radiology", "specialty:radiology", "radiology", "Radiology", "company:rapidai", "rapidai", "RapidAI", "linked_curated_company", "source_vendor_slug", "imaging-diagnostics", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K261085", "source_link_and_verification_date", "none", "2026-10-03" ], [ "fda-510k:K253751", "K253751", "CXRDetectAI", "Neurocareai, Inc. (Dba Savelife.Ai)", "manufacturer:neurocareai-inc-dba-savelife-ai", "neurocareai-inc-dba-savelife-ai", "TX", "US", "2026-07-08", 2026, "last_24_months", "Substantially Equivalent", "Radiology", 1, "QFM", "device-class:radiological-computer-assisted-prioritization-software-for-lesions-qfm", "radiological-computer-assisted-prioritization-software-for-lesions-qfm", "AI Lesion Prioritization Software for Radiology", "specialty:radiology", "radiology", "Radiology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K253751", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K253704", "K253704", "iPredict-DR", "iHealthscreen, Inc.", "manufacturer:ihealthscreen-inc", "ihealthscreen-inc", "NY", "US", "2026-07-02", 2026, "last_24_months", "Substantially Equivalent", "Ophthalmic", 1, "PIB", "device-class:diabetic-retinopathy-detection-device-pib", "diabetic-retinopathy-detection-device-pib", "Diabetic Retinopathy Detection AI", "specialty:ophthalmic", "ophthalmic", "Ophthalmic", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K253704", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K253884", "K253884", "Koios DS (3.8)", "Koios Medical, Inc.", "manufacturer:koios-medical-inc", "koios-medical-inc", "NY", "US", "2026-07-02", 2026, "last_24_months", "Substantially Equivalent", "Radiology", 1, "POK", "device-class:computer-assisted-diagnostic-software-for-lesions-suspicious-for-cancer-pok", "computer-assisted-diagnostic-software-for-lesions-suspicious-for-cancer-pok", "AI Diagnostic Software for Suspicious Lesions", "specialty:radiology", "radiology", "Radiology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K253884", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K260714", "K260714", "MammoScreen® (5)", "Therapixel", "manufacturer:therapixel", "therapixel", "", "FR", "2026-06-26", 2026, "last_24_months", "Substantially Equivalent", "Radiology", 1, "QDQ", "device-class:radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "AI Cancer Detection Software for Radiology", "specialty:radiology", "radiology", "Radiology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260714", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K260729", "K260729", "Vascular Assist Occlusion Triage (VAOT) (v1.0)", "GuideAI Health", "manufacturer:guideai-health", "guideai-health", "MA", "US", "2026-06-18", 2026, "last_24_months", "Substantially Equivalent", "Radiology", 1, "QAS", "device-class:radiological-computer-assisted-triage-and-notification-software-qas", "radiological-computer-assisted-triage-and-notification-software-qas", "AI Triage and Notification Software for Radiology", "specialty:radiology", "radiology", "Radiology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260729", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K253825", "K253825", "Saige-Dx", "DeepHealth, Inc.", "manufacturer:deephealth-inc", "deephealth-inc", "MA", "US", "2026-06-15", 2026, "last_24_months", "Substantially Equivalent", "Radiology", 1, "QDQ", "device-class:radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq", "AI Cancer Detection Software for Radiology", "specialty:radiology", "radiology", "Radiology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K253825", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K260332", "K260332", "EchoNext", "Pathwai, Inc.", "manufacturer:pathwai-inc", "pathwai-inc", "NY", "US", "2026-06-08", 2026, "last_24_months", "Substantially Equivalent", "Cardiovascular", 1, "QXO", "device-class:cardiovascular-machine-learning-based-notification-software-qxo", "cardiovascular-machine-learning-based-notification-software-qxo", "Cardiovascular Machine Learning Notification Software", "specialty:cardiovascular", "cardiovascular", "Cardiovascular", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K260332", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ], [ "fda-510k:K261519", "K261519", "Sonio Suspect", "Sonio", "manufacturer:sonio", "sonio", "", "FR", "2026-06-04", 2026, "last_24_months", "Substantially Equivalent", "Radiology", 1, "POK", "device-class:computer-assisted-diagnostic-software-for-lesions-suspicious-for-cancer-pok", "computer-assisted-diagnostic-software-for-lesions-suspicious-for-cancer-pok", "AI Diagnostic Software for Suspicious Lesions", "specialty:radiology", "radiology", "Radiology", "", "", "", "normalized_applicant_only", "none", "", "FDA 510(k)", "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K261519", "source_link_and_verification_date", "curated_company_link_missing", "2026-10-03" ] ] }, "manufacturers": { "record_type": "entity", "columns": [ "applicant_id", "applicant_slug", "applicant_name", "applicant_name_variants", "clearance_count", "device_class_count", "specialty_count", "product_codes", "device_class_ids", "specialty_ids", "first_clearance", "latest_clearance", "linked_company_ids", "company_link_status", "source_type", "provenance_status", "quality_flags", "last_verified" ], "records": [ [ "manufacturer:a2z-radiology-ai-inc", "a2z-radiology-ai-inc", "A2z Radiology Ai, Inc.", "A2z Radiology Ai, Inc.", 2, 1, 1, "QAS", "device-class:radiological-computer-assisted-triage-and-notification-software-qas", "specialty:radiology", "2025-11-24", "2026-09-16", "", "normalized_applicant_only", "FDA 510(k) applicant aggregation", "derived_from_fda_clearance_records", "curated_company_link_missing", "2026-10-03" ], [ "manufacturer:aeye-health-inc", "aeye-health-inc", "Aeye Health, Inc.", "Aeye Health, Inc.", 2, 1, 1, "PIB", "device-class:diabetic-retinopathy-detection-device-pib", "specialty:ophthalmic", "2022-11-10", "2024-04-23", "", "normalized_applicant_only", "FDA 510(k) applicant aggregation", "derived_from_fda_clearance_records", "curated_company_link_missing", "2026-10-03" ], [ "manufacturer:aidoc-medical-ltd", "aidoc-medical-ltd", "Aidoc Medical , Ltd.", "Aidoc Medical , Ltd.", 30, 2, 1, "QAS | QFM", "device-class:radiological-computer-assisted-prioritization-software-for-lesions-qfm | device-class:radiological-computer-assisted-triage-and-notification-software-qas", "specialty:radiology", "2018-08-01", "2026-05-14", "company:aidoc", "single_curated_company", "FDA 510(k) applicant aggregation", "derived_from_fda_clearance_records", "none", "2026-10-03" ], [ "manufacturer:aisap", "aisap", "Aisap", "Aisap", 1, 1, 1, "POK", "device-class:computer-assisted-diagnostic-software-for-lesions-suspicious-for-cancer-pok", "specialty:radiology", "2024-08-01", "2024-08-01", "", "normalized_applicant_only", "FDA 510(k) applicant aggregation", "derived_from_fda_clearance_records", "curated_company_link_missing", "2026-10-03" ], [ "manufacturer:analytics-for-life-inc", "analytics-for-life-inc", "Analytics For Life, Inc.", "Analytics For Life, Inc.", 1, 1, 1, "SAT", "device-class:pulmonary-hypertension-machine-learning-based-notification-software-sat", "specialty:cardiovascular", "2024-04-05", "2024-04-05", "", "normalized_applicant_only", "FDA 510(k) applicant aggregation", "derived_from_fda_clearance_records", "curated_company_link_missing", "2026-10-03" ], [ "manufacturer:annalise-ai", "annalise-ai", "Annalise-Ai", "Annalise-Ai", 2, 1, 1, "QFM", "device-class:radiological-computer-assisted-prioritization-software-for-lesions-qfm", "specialty:radiology", "2022-02-24", "2025-04-23", "company:annalise-ai", "single_curated_company", "FDA 510(k) applicant aggregation", "derived_from_fda_clearance_records", "none", "2026-10-03" ], [ "manufacturer:annalise-ai-pty-ltd", "annalise-ai-pty-ltd", "Annalise-Ai Pty , Ltd.", "Annalise-Ai Pty , Ltd.", 6, 2, 1, "QAS | QFM", "device-class:radiological-computer-assisted-prioritization-software-for-lesions-qfm | device-class:radiological-computer-assisted-triage-and-notification-software-qas", "specialty:radiology", "2023-03-28", "2023-09-22", "company:annalise-ai", "single_curated_company", "FDA 510(k) applicant aggregation", "derived_from_fda_clearance_records", "none", "2026-10-03" ], [ "manufacturer:anumana-inc", "anumana-inc", "Anumana, Inc.", "Anumana, Inc.", 4, 3, 1, "QYE | SAT | SHP", "device-class:cardiac-amyloidosis-machine-learning-based-notification-software-shp | device-class:pulmonary-hypertension-machine-learning-based-notification-software-sat | device-class:reduced-ejection-fraction-machine-learning-based-notification-software-qye", "specialty:cardiovascular", "2023-09-28", "2026-04-07", "", "normalized_applicant_only", "FDA 510(k) applicant aggregation", "derived_from_fda_clearance_records", "curated_company_link_missing", "2026-10-03" ], [ "manufacturer:apple-inc", "apple-inc", "Apple, Inc.", "Apple, Inc.", 1, 1, 1, "SFR", 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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.", "FDA product classification and 510(k) records", "https://open.fda.gov/apis/device/510k/", "source_link_and_verification_date", "none", "2026-10-03" ], [ "device-class:chest-x-ray-computer-aided-detection-omj", "chest-x-ray-computer-aided-detection-omj", "Chest X-Ray Computer-Aided Detection", "OMJ", "specialty:radiology", "radiology", "Radiology", "Chest X-Ray Computer Aided Detection", "2", "892.2050", "1", "", "", 1, 1, 1, 1, 0, "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.", "FDA product classification and 510(k) records", "https://open.fda.gov/apis/device/510k/", "source_link_and_verification_date", "none", "2026-10-03" ], [ 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device-class:reduced-ejection-fraction-machine-learning-based-notification-software-qye", "2023-08-03", "2026-08-21", "Heart and vessel AI that watches for one named condition and raises a hand. Each product here is cleared for one specific warning.", "AI Healthcare Now specialty grouping derived from FDA records", "verification_date_only", "none", "2026-10-03" ], [ "specialty:gastroenterology-urology", "gastroenterology-urology", "Gastroenterology, Urology", "Gastroenterology, Urology", 1, 1, 23, 23, 8, 0, "QNP", "device-class:gastrointesinal-lesion-software-detection-system-qnp", "2021-04-09", "2026-09-12", "Colonoscopy software that flags possible lesions live, while the scope is still moving.", "AI Healthcare Now specialty grouping derived from FDA records", "verification_date_only", "none", "2026-10-03" ], [ "specialty:neurology", "neurology", "Neurology", "Neurology", 1, 1, 6, 6, 3, 0, "QPF", "device-class:pediatric-autism-spectrum-disorder-diagnosis-aid-qpf", "2021-06-02", "2026-03-05", "A short list, led by software cleared to help diagnose autism in young children.", "AI Healthcare Now specialty grouping derived from FDA records", "verification_date_only", "none", "2026-10-03" ], [ "specialty:ophthalmic", "ophthalmic", "Ophthalmic", "Ophthalmic", 1, 1, 8, 8, 5, 0, "PIB", "device-class:diabetic-retinopathy-detection-device-pib", "2018-04-11", "2026-07-02", "Eye screening AI, including the first products cleared to give a result without a specialist reading the image.", "AI Healthcare Now specialty grouping derived from FDA records", "verification_date_only", "none", "2026-10-03" ], [ "specialty:pathology", "pathology", "Pathology", "Pathology", 4, 4, 5, 5, 4, 0, "QPN | QYV | SFH | SHW", "device-class:digital-cervical-cytology-slide-imaging-system-with-artificial-intelligence-algorithm-qyv | device-class:pathology-software-algorithm-device-analyzing-digital-images-for-breast-cancer-prognosis-shw | device-class:pathology-software-algorithm-device-analyzing-digital-images-for-prostate-cancer-prognosis-sfh | device-class:software-algorithm-device-to-assist-users-in-digital-pathology-qpn", "2021-09-21", "2026-05-04", "Software that reads digitized slides. Small in number, and the first products cleared to help predict how a cancer will behave.", "AI Healthcare Now specialty grouping derived from FDA records", "verification_date_only", "none", "2026-10-03" ], [ "specialty:radiology", "radiology", "Radiology", "Radiology", 10, 10, 238, 238, 99, 5, "NWE | OEB | OMJ | POK | QAS | QBS | QDQ | QFM | QJU | QVD", "device-class:chest-x-ray-computer-aided-detection-omj | device-class:colon-computed-tomography-system-computer-aided-detection-nwe | device-class:computer-assisted-diagnostic-software-for-lesions-suspicious-for-cancer-pok | device-class:image-acquisition-and-or-optimization-guided-by-artificial-intelligence-qju | device-class:lung-computed-tomography-system-computer-aided-detection-oeb | device-class:radiological-computer-assisted-detection-diagnosis-software-for-fracture-qbs | device-class:radiological-computer-assisted-detection-diagnosis-software-for-lesions-suspicious-for-cancer-qdq | device-class:radiological-computer-assisted-prioritization-software-for-lesions-qfm | device-class:radiological-computer-assisted-triage-and-notification-software-qas | device-class:radiological-machine-learning-based-quantitative-imaging-software-with-change-control-plan-qvd", "2003-11-06", "2026-09-16", "Most cleared healthcare AI reads pictures. This is where the scans live, and it is by far the busiest field on the list.", "AI Healthcare Now specialty grouping derived from FDA records", "verification_date_only", "none", "2026-10-03" ] ] }, "learning_programs": { "record_type": "entity", "columns": [ "record_id", "slug", "title", "provider", "credential", "who_it_suits", "description", "url", "link_status", "link_checked", "source_type", "provenance_status", "quality_flags", "last_verified" ], "records": [ [ "learning-program:abpm-clinical-informatics", "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", "Official learning program page", "source_link_and_verification_date", "none", "2026-09-28" ], [ "learning-program:acr-data-science-institute", "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", "Official learning program page", "source_link_and_verification_date", "none", "2026-09-28" ], [ "learning-program:ahima-health-information", "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", "Official learning program page", "source_link_and_verification_date", "none", "2026-09-28" ], [ "learning-program:amia-10x10", "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", "Official learning program page", "source_link_and_verification_date", "none", "2026-09-28" ], [ "learning-program:coursera-ai-for-medicine", "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", "Official learning program page", "source_link_and_verification_date", "none", "2026-09-28" ] ] }, "career_roles": { "record_type": "entity", "columns": [ "record_id", "slug", "title", "one_line", "employer_side", "remote_reality", "what_you_do", "background", "skills", "ai_exposure", "canonical_url", "source_type", "provenance_status", "quality_flags", "last_verified" ], "records": [ [ "career-role:ai-governance-lead", "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/", "AI Healthcare Now curated career profile", "source_link_and_verification_date", "none", "2026-09-28" ], [ "career-role:clinical-ai-lead", "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/", "AI Healthcare Now curated career profile", "source_link_and_verification_date", "none", "2026-09-28" ], [ "career-role:clinical-documentation-specialist", "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/", "AI Healthcare Now curated career profile", "source_link_and_verification_date", "none", "2026-09-28" ], [ "career-role:clinical-evidence-lead", "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/", "AI Healthcare Now curated career profile", "source_link_and_verification_date", "none", "2026-09-28" ], [ "career-role:clinical-implementation-manager", "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/", "AI Healthcare Now curated career profile", "source_link_and_verification_date", "none", "2026-09-28" ] ] }, "evidence_topics": { "record_type": "entity", "columns": [ "record_id", "slug", "title", "linked_group", "query", "total_indexed", "declared_study_count", "derived_study_count", "oldest_year", "newest_year", "design_mix", "pmid_count", "doi_count", "open_access_count", "journal_count", "cited_by_total", "description", "source_type", "source_url", "provenance_status", "quality_flags", "last_verified" ], "records": [ [ "research-topic:ambient-ai-documentation", "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, 24, 2018, "2025", "16 | 3 | 2 | 1 | 1 | 1", 24, 24, 17, 16, 1779, "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.", "Europe PMC topic collection", "https://europepmc.org/", "source_link_and_verification_date", "none", "2026-10-03" ], [ "research-topic:breast-cancer-detection", "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, 24, 2000, "2023", "21 | 2 | 1", 24, 24, 4, 14, 7955, "Screening mammography AI, the oldest research base in the field and the one with the largest prospective trials.", "Europe PMC topic collection", "https://europepmc.org/", "source_link_and_verification_date", "none", "2026-10-03" ], [ "research-topic:colonoscopy-polyp-detection", "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, 24, 2016, "2025", "13 | 7 | 3 | 1", 24, 24, 5, 13, 5598, "Software that highlights possible polyps on the live scope view. One of the few areas with a solid stack of randomized trials.", "Europe PMC topic collection", "https://europepmc.org/", "source_link_and_verification_date", "none", "2026-10-03" ], [ "research-topic:diabetic-retinopathy-screening", "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, 24, 2013, "2022", "19 | 5", 24, 24, 8, 17, 7782, "Eye screening software, including systems cleared to give a result without a specialist reading the image. The deepest evidence base in autonomous AI.", "Europe PMC topic collection", "https://europepmc.org/", "source_link_and_verification_date", "none", "2026-10-03" ], [ "research-topic:healthcare-ai-roi", "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, 24, 1998, "2025", "20 | 2 | 1 | 1", 24, 24, 10, 23, 1713, "Published cost-effectiveness and economic evaluations of healthcare AI. A short list, which is itself the finding.", "Europe PMC topic collection", "https://europepmc.org/", "source_link_and_verification_date", "none", "2026-10-03" ] ] }, "evidence_studies": { "record_type": "entity", "columns": [ "record_id", "relationship_count", "topic_ids", "topic_slugs", "topic_titles", "study_title", "authors", "journal", "year", "design", "source_id_type", "source_id", "pmid", "doi", "cited_by", "open_access", "source_type", "url", "provenance_status", "quality_flags" ], "records": [ [ "pmid:39500346", 1, "research-topic:ambient-ai-documentation", "ambient-ai-documentation", "Ambient AI Documentation", "The Effect of Ambient Artificial Intelligence Notes on Provider Burnout.", "Misurac J and 2 others", "Applied clinical informatics", "2025", "Study", "pmid", "39500346", "39500346", "10.1055/a-2461-4576", 38, false, "Europe PMC bibliographic record", "https://europepmc.org/article/MED/39500346", "source_link_present", "none" ], [ "pmid:39657021", 1, "research-topic:ambient-ai-documentation", "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", "pmid", "39657021", "39657021", "10.1093/jamia/ocae295", 142, false, "Europe PMC bibliographic record", "https://europepmc.org/article/MED/39657021", "source_link_present", "none" ], [ "pmid:39688515", 1, "research-topic:ambient-ai-documentation", "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", "pmid", "39688515", "39688515", "10.1093/jamia/ocae304", 124, false, "Europe PMC bibliographic record", "https://europepmc.org/article/MED/39688515", "source_link_present", "none" ], [ "pmid:39823022", 1, "research-topic:ambient-ai-documentation", "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", "pmid", "39823022", "39823022", "10.1097/gox.0000000000006450", 62, true, "Europe PMC bibliographic record", "https://europepmc.org/article/MED/39823022", "source_link_present", "none" ], [ "pmid:39969880", 1, "research-topic:ambient-ai-documentation", "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", "pmid", "39969880", "39969880", "10.1001/jamanetworkopen.2024.60637", 133, true, "Europe PMC bibliographic record", "https://europepmc.org/article/MED/39969880", "source_link_present", "none" ], [ "pmid:39991073", 1, "research-topic:ambient-ai-documentation", "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", "pmid", "39991073", "39991073", "10.1093/jamiaopen/ooaf013", 78, true, "Europe PMC bibliographic record", "https://europepmc.org/article/MED/39991073", "source_link_present", "none" ], [ "pmid:40126477", 1, "research-topic:ambient-ai-documentation", "ambient-ai-documentation", "Ambient AI Documentation", "Physician Perspectives on Ambient AI Scribes.", "Shah SJ and 14 others", "JAMA network open", "2025", "Study", "pmid", "40126477", "40126477", "10.1001/jamanetworkopen.2025.1904", 111, true, "Europe PMC bibliographic record", "https://europepmc.org/article/MED/40126477", "source_link_present", "none" ], [ "pmid:40306686", 1, "research-topic:ambient-ai-documentation", "ambient-ai-documentation", "Ambient AI Documentation", "Clinical Implementation of Artificial Intelligence Scribes in Health Care: A Systematic Review.", "Hassan H and 12 others", "Applied clinical informatics", "2025", "Systematic review", "pmid", "40306686", "40306686", "10.1055/a-2597-2017", 38, false, "Europe PMC bibliographic record", "https://europepmc.org/article/MED/40306686", "source_link_present", "none" ], [ "pmid:40314951", 1, "research-topic:ambient-ai-documentation", "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", "pmid", "40314951", "40314951", "10.1001/jamanetworkopen.2025.8614", 105, true, "Europe PMC bibliographic record", "https://europepmc.org/article/MED/40314951", "source_link_present", "none" ], [ "pmid:40565474", 1, "research-topic:ambient-ai-documentation", "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", "pmid", "40565474", "40565474", "10.3390/healthcare13121447", 56, true, "Europe PMC bibliographic record", "https://europepmc.org/article/MED/40565474", "source_link_present", "none" ], [ "pmid:40700466", 1, "research-topic:ambient-ai-documentation", "ambient-ai-documentation", "Ambient AI Documentation", "Evaluating the Usability, Technical Performance, and Accuracy of Artificial Intelligence Scribes for Primary Care: Competitive Analysis.", "Ha E and 6 others", "JMIR human factors", "2025", "Study", "pmid", "40700466", "40700466", "10.2196/71434", 29, true, "Europe PMC bibliographic record", "https://europepmc.org/article/MED/40700466", "source_link_present", "none" ], [ "pmid:40749188", 1, "research-topic:ambient-ai-documentation", "ambient-ai-documentation", "Ambient AI Documentation", "AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration.", "Leung TI and 2 others", "JMIR medical informatics", "2025", "Study", "pmid", "40749188", "40749188", "10.2196/80898", 35, true, "Europe PMC bibliographic record", "https://europepmc.org/article/MED/40749188", "source_link_present", "none" ], [ "pmid:40816301", 1, "research-topic:colonoscopy-polyp-detection", "colonoscopy-polyp-detection", "AI Polyp Detection in Colonoscopy", "Endoscopist deskilling risk after exposure to artificial intelligence in colonoscopy: a multicentre, observational study.", "Budzyń K and 20 others", "The lancet. Gastroenterology & hepatology", "2025", "Study", "pmid", "40816301", "40816301", "10.1016/s2468-1253(25)00133-5", 159, false, "Europe PMC bibliographic record", "https://europepmc.org/article/MED/40816301", "source_link_present", "none" ], [ "pmid:40839265", 1, "research-topic:ambient-ai-documentation", "ambient-ai-documentation", "Ambient AI Documentation", "Ambient Documentation Technology in Clinician Experience of Documentation Burden and Burnout.", "You JG and 25 others", "JAMA network open", "2025", "Study", "pmid", "40839265", "40839265", "10.1001/jamanetworkopen.2025.28056", 49, true, "Europe PMC bibliographic record", "https://europepmc.org/article/MED/40839265", "source_link_present", "none" ], [ "pmid:40858882", 1, "research-topic:healthcare-ai-roi", "healthcare-ai-roi", "Cost and Return on Healthcare AI", "Systematic review of cost effectiveness and budget impact of artificial intelligence in healthcare.", "El Arab RA and 1 others", "NPJ digital medicine", "2025", "Systematic review", "pmid", "40858882", "40858882", "10.1038/s41746-025-01722-y", 70, true, "Europe PMC bibliographic record", "https://europepmc.org/article/MED/40858882", "source_link_present", "none" ] ] } }, "codebook": { "dataset": "healthcare-ai-market-fda-dataset", "version": "1.1.0", "release_date": "2026-10-08", "row_count_model": { "entity_records": "Unique source or normalized entities across the nine entity tables.", "relationship_records": "Explicit device-to-manufacturer-to-class-to-specialty-to-company links plus citation-to-topic links. These rows repeat entity identifiers so buyers can join the tables directly.", "total_records": "Entity records plus relationship records." }, "tables": { "devices": { "record_type": "entity", "columns": [ "record_id", "k_number", "device_name", "applicant", "applicant_id", "applicant_slug", "state", "country", "decision_date", "decision_year", "clearance_recency_band", "decision", "review_panel", "relationship_count", "product_codes", "device_class_ids", "device_class_slugs", "device_class_titles", "specialty_ids", "specialty_slugs", "specialty_labels", "company_id", "company_slug", "company_name", "company_link_status", "company_match_method", "vendor_group", "source_type", "source_url", "provenance_status", "quality_flags", "last_verified" ], "record_count": 295 }, "manufacturers": { "record_type": "entity", "columns": [ "applicant_id", "applicant_slug", "applicant_name", "applicant_name_variants", "clearance_count", "device_class_count", "specialty_count", "product_codes", "device_class_ids", "specialty_ids", "first_clearance", "latest_clearance", "linked_company_ids", "company_link_status", "source_type", "provenance_status", "quality_flags", "last_verified" ], "record_count": 126 }, "relationships": { "record_type": "relationship", "columns": [ "relationship_id", "device_record_id", "k_number", "applicant_id", "applicant_slug", "manufacturer_name", "device_class_id", "device_class_slug", "device_class_title", "specialty_id", "specialty_slug", "specialty_label", "company_id", "company_slug", "company_name", "product_code", "decision_date", "company_link_status", "company_match_method", "source_url", "provenance_status", "quality_flags" ], "record_count": 295 }, "research_relationships": { "record_type": "relationship", "columns": [ "relationship_id", "citation_record_id", "topic_id", "topic_slug", "topic_title", "study_title", "year", "source_id_type", "source_id", "url", "provenance_status", "quality_flags" ], "record_count": 192 }, "device_classes": { "record_type": "entity", "columns": [ "record_id", "slug", "title", "product_code", "specialty_id", "specialty_slug", "specialty_label", "fda_device_name", "device_class", "regulation_number", "submission_type", "alias_slugs", "alias_titles", "source_record_count", "clearance_count", "derived_clearance_count", "applicant_count", "linked_company_count", "first_clearance", "latest_clearance", "definition", "plain_summary", "source_type", "source_url", "provenance_status", "quality_flags", "last_verified" ], "record_count": 25 }, "companies": { "record_type": "entity", "columns": [ "record_id", "slug", "name", "category", "company_structure", "market_access", "public_market_access", "issuer_name", "ticker", "exchange", "relationship_to_security", "linked_clearance_count", "linked_device_class_count", "linked_specialty_count", "linked_product_codes", "linked_applicant_names", "first_linked_clearance", "latest_linked_clearance", "company_link_basis", "official_url", "profile_url", "careers_url", "investor_relations_url", "source_type", "provenance_status", "quality_flags", "last_verified" ], "record_count": 35 }, "specialties": { "record_type": "entity", "columns": [ "record_id", "slug", "title", "review_panel", "declared_class_count", "derived_class_count", "declared_clearance_count", "derived_clearance_count", "applicant_count", "linked_company_count", "product_codes", "device_class_ids", "first_clearance", "latest_clearance", "description", "source_type", "provenance_status", "quality_flags", "last_verified" ], "record_count": 6 }, "learning_programs": { "record_type": "entity", "columns": [ "record_id", "slug", "title", "provider", "credential", "who_it_suits", "description", "url", "link_status", "link_checked", "source_type", "provenance_status", "quality_flags", "last_verified" ], "record_count": 10 }, "career_roles": { "record_type": "entity", "columns": [ "record_id", "slug", "title", "one_line", "employer_side", "remote_reality", "what_you_do", "background", "skills", "ai_exposure", "canonical_url", "source_type", "provenance_status", "quality_flags", "last_verified" ], "record_count": 10 }, "evidence_topics": { "record_type": "entity", "columns": [ "record_id", "slug", "title", "linked_group", "query", "total_indexed", "declared_study_count", "derived_study_count", "oldest_year", "newest_year", "design_mix", "pmid_count", "doi_count", "open_access_count", "journal_count", "cited_by_total", "description", "source_type", "source_url", "provenance_status", "quality_flags", "last_verified" ], "record_count": 8 }, "evidence_studies": { "record_type": "entity", "columns": [ "record_id", "relationship_count", "topic_ids", "topic_slugs", "topic_titles", "study_title", "authors", "journal", "year", "design", "source_id_type", "source_id", "pmid", "doi", "cited_by", "open_access", "source_type", "url", "provenance_status", "quality_flags" ], "record_count": 189 } }, "enrichment_fields": { "record_id": "Stable namespaced identifier for a source or normalized entity.", "applicant_id": "Normalized FDA applicant identifier. Punctuation-only name variants resolve to the same ID.", "relationship_id": "Stable identifier for one device or research relationship row.", "company_link_status": "States whether the source already supplied a curated company link or only a normalized FDA applicant identity.", "company_match_method": "Method used for the company connection. Version 1.1 uses source_vendor_slug and never invents a fuzzy match.", "clearance_recency_band": "Decision-date group measured against the release date: last 24 months, 2 to 5 years, or over 5 years.", "provenance_status": "Plain status describing whether a source link and verification date are present.", "quality_flags": "Pipe-delimited data-quality notes. The value none means no defined flag fired.", "relationship_count": "Number of device-class relationships carried by one unique FDA clearance entity.", "alias_slugs": "Earlier source slugs folded into the current canonical device-class record.", "source_record_count": "Number of source device-class records represented by one canonical class entity.", "topic_ids": "Stable research-topic identifiers connected to one normalized citation." }, "quality_flag_definitions": { "curated_company_link_missing": "The source record has a normalized FDA applicant identity but no curated company slug.", "multiple_curated_company_links": "One normalized applicant identity connects to more than one curated company slug.", "source_url_missing": "The source row does not include a source URL.", "verification_date_missing": "The curated source row does not include a verification date.", "decision_date_missing_or_invalid": "The FDA decision date is blank or does not use YYYY-MM-DD.", "multiple_device_class_relationships": "One FDA clearance connects to more than one device-class record. The device stays unique while the relationship table keeps each class connection.", "source_class_aliases_collapsed": "Two or more source class records share one FDA product code and regulation number. The newest verified record is canonical and the earlier slugs remain in alias_slugs.", "declared_clearance_count_mismatch": "The source summary count differs from the records packaged in this release.", "declared_class_count_mismatch": "The source specialty class count differs from the class IDs derived from packaged records.", "declared_study_count_mismatch": "The source topic study count differs from the citations packaged in this release.", "standard_publication_id_missing": "A research citation does not have a PMID or DOI, so its stable ID is derived from the topic, title, and year." }, "relationship_rules": [ "FDA applicant names are normalized only for case, punctuation, spacing, and readable slug creation.", "A device connects to a curated company only when the source device record carries a vendor_slug that exists in the curated company collection.", "Version 1.1 does not use fuzzy name matching to infer a company relationship.", "Device-class records sharing one FDA product code and regulation number are folded into the newest verified class while earlier slugs and titles remain visible as aliases.", "Research citations sharing one PMID or DOI are stored once, with each topic connection preserved in research_relationships." ], "boundaries": [ "No patient records, protected health information, claims, diagnoses, treatment outcomes, or clinical predictions.", "Research 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.", "Research 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." ] } }