The Frontline of Medical AI # Radiology is where artificial intelligence meets clinical medicine at scale. With over 870 FDA-cleared AI algorithms, representing 78% of all medical AI approvals, radiology is both the proving ground and the liability frontier for AI in healthcare. When these algorithms miss cancers, misidentify strokes, or generate false positives that lead to unnecessary interventions, radiologists and healthcare systems face mounting legal exposure.
The High Stakes of Diagnostic AI # When artificial intelligence gets a diagnosis wrong, the consequences can be catastrophic. Missed cancers, delayed stroke treatment, sepsis alerts that fail to fire, diagnostic AI failures are increasingly documented, yet lawsuits directly challenging these systems remain rare. This tracker compiles the evidence: validated failures, performance gaps, bias documentation, FDA recalls, and the emerging litigation that will shape AI medical liability for decades.
Healthcare represents the highest-stakes arena for AI standard of care questions. When diagnostic AI systems, clinical decision support tools, and treatment recommendation algorithms are wrong, patients die. With over 1,250 FDA-authorized AI medical devices and AI-related malpractice claims rising 14% since 2022, understanding the evolving standard of care is critical for patients, providers, and institutions.
Executive Summary # AI medical devices are proliferating faster than regulatory infrastructure can track their failures. With over 1,200 FDA-authorized AI devices and a 14% increase in AI-related malpractice claims since 2022, understanding the liability landscape has never been more critical.