4 papers
AI Morbidity and Mortality: A Framework for Clinical AI Failure Review
Paulius Mui, Dean F. Sittig, Steve Labkoff +1
Clinical artificial intelligence is increasingly embedded in real-world care, yet existing safety mechanisms are poorly suited to reconstructing and learning from individual AI-rel…
End-to-End Evaluation and Governance of an EHR-Embedded AI Agent for Clinicians
Aaryan Shah, Andrew Hines, Alexia Downs +6
Clinical AI systems require not just point-in-time evaluation but continuous governance: the ongoing practice of monitoring, evaluating, iterating, and re-evaluating performance th…
Case-Specific Rubrics for Clinical AI Evaluation: Methodology, Validation, and LLM-Clinician Agreement Across 823 Encounters
Aaryan Shah, Andrew Hines, Alexia Downs +6
Objective. Clinical AI documentation systems require evaluation methodologies that are clinically valid, economically viable, and sensitive to iterative changes. Methods requiring…
Explainable AI as a Double-Edged Sword in Dermatology: The Impact on Clinicians versus The Public
Xuhai Xu, Haoyu Hu, Haoran Zhang +21
Artificial intelligence (AI) is increasingly permeating healthcare, from physician assistants to consumer applications. Since AI algorithm's opacity challenges human interaction, e…