FDA Clearance & Incident Tracker
Tracker
A dated, filterable log of new FDA AI/ML device clearances, recalls, and reported clinical-AI incidents, sourced from FDA's AI-enabled device list, MAUDE reports, and other cited primary sources such as ECRI hazard reports. This is the site's freshness engine: every entry is timestamped, tagged by specialty and clearance pathway, states its sourcing and known limitations (e.g., MAUDE under-reporting, self-reported and unconfirmed incident causation), and links to any existing appraisal covering that device or tool category. Excludes narrative evaluation of evidence quality, which belongs to Appraisals, and excludes editorializing on fault or causation for incident entries.
Sourced from FDA's AI-enabled device list, MAUDE reports, and ECRI-style hazard reporting. MAUDE is self-reported and known to under-report; reported-incident entries do not confirm causation. Full sourcing and limitations are disclosed on Methodology.
EntryBeyond the Hype: How 2026 AI in Healthcare Summits Are Pivoting to Governance, Regulation, and Real-World ROI
EntryThe AI Healthcare Market's Regulatory Crossroads: How FDA Clearances, Joint Commission Guidelines, and the EU AI Act Shape Commercial Prospects in 2026
EntryAI in Healthcare by the Numbers: 100+ Statistics on Adoption, Market Size, Clinical Accuracy, ROI, and Risk (2026)
EntryThe Regulatory Flashpoint Over AI in Prior Authorization and Claims Review: State Laws, Federal Preemption, and the Compliance Burden in 2026
EntryThe Evidence Base for Healthcare Conversational AI: What Clinical Studies Actually Show
EntryThe AI Healthcare Stack: Mapping the 20 Most Important Companies by Category in 2026
EntryFrom $39B to $1T: What's Driving and What's Constraining the AI Healthcare Market in 2026
EntryAI in Healthcare Administration in 2026: Adoption Benchmarks, Cost Savings, and the Evidence Behind the Hype
EntryGenerative AI in Healthcare 2026: Market, Regulation, and the Shadow AI Governance Challenge
EntryFrom Evidence Gaps to Lifecycle Oversight: How the FDA is Reshaping AI Medical Device Regulation Through PCCPs, TPLC, and Transparency Requirements
EntryThe Patchwork Landscape: How US Federal and State Governments Are Regulating AI in Public Health in 2026
EntryThe New Economics of Health Tech AI: How AI-Native Companies Are Compressing Time-to-Scale and Reshaping Venture Investing
EntryAI in Revenue Cycle Management: Navigating the New FCA and OIG Compliance Landscape
EntryAlgorithmic Bias in Public Health AI: The Contested Regulatory Response to Automated Disparities
EntryGenerative AI in Healthcare: State of the Evidence and Policy Landscape in 2026
EntryAI in Healthcare 2026: A State-of-the-Industry Evidence Assessment
EntryHealth Tech AI in 2026: Where Investment, Adoption, and ROI Data Converge — and Where the Gaps Remain
EntryThe 2026 AI in Healthcare Summit Landscape: A Strategic Guide to Major Events, Themes, and Takeaways
EntryThe Administrative AI Paradox: Why Automation Is Driving Up Healthcare Costs in 2026
EntryThe AI Arms Race in Health Insurance Utilization Review: How Insurers Are Using AI for Prior Authorization, What the Evidence Shows, and Why Regulators Are Stepping In
EntryAI in Revenue Cycle Management: The ROI Evidence from Health Systems
EntryThe Competitive Landscape of AI in Healthcare 2026: Big Tech, Startups, and the EHR Counteroffensive
EntryCMS AI Reimbursement Policy: Coverage Decisions for AI-Assisted Diagnostics
EntryFDA AI/ML SaMD Guidance Status as of June 2026: What Is Final, What Is Draft, and What Comes Next
EntryAI Bias in Emergency Medicine: Evidence and Equity Gaps