A Clinician’s Framework for Evaluating AI Before It Reaches Patient Care
A practical five-part framework for examining intended use, evidence, workflow, oversight and ongoing monitoring.
8 min read · Updated July 30, 2026Read article
AI for DoctorsInstituteExplore coursesOriginal analysis by Andrie Udal, PhD, MSHDS, grounded in primary guidance from medical, public-health and regulatory organizations.
Educational content—not medical, legal or regulatory advice.
A practical five-part framework for examining intended use, evidence, workflow, oversight and ongoing monitoring.
8 min read · Updated July 30, 2026Read articleA safety-oriented guide to approved environments, minimum-necessary data, de-identification and clinical review.
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6 min read · Updated July 30, 2026Read articleThese links are included for public benefit. The Institute receives no commission for them.
Global principles addressing autonomy, safety, transparency, accountability, equity and sustainability.
Open official source ↗U.S. Food and Drug AdministrationA periodically updated list and regulatory context for AI-enabled medical devices authorized in the United States.
Open official source ↗Association of American Medical CollegesNational work to define AI competencies across undergraduate, graduate and continuing medical education.
Open official source ↗National Institute of Standards and TechnologyA voluntary framework for identifying, measuring and managing risks across the AI lifecycle.
Open official source ↗U.S. Department of Health and Human ServicesAuthoritative information for covered entities and professionals working with protected health information.
Open official source ↗American Medical AssociationAMA policy supporting standardized AI training and continuing education for physicians.
Open official source ↗