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The physician as a catalyst

Reimagining medical education for an AI era

Bibliographic Data

ID21448138
AuthorsMilit S Patel (0009-0000-9179-267X, The University of Texas at Austin), Edward Christopher Dee (0000-0001-6119-0889, Memorial Sloan Kettering Cancer Center), Samarra Toby (Prince Charles Hospital), Mena Ramos (0009-0000-7032-1529, University of California, San Francisco), Leo Anthony Celi (0000-0001-6712-6626, Massachusetts Institute of Technology, corresponding author)
Year2026
Pages1-7
Publication date2026-04-10
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueMedical Teacher (JOURNAL)
Journal identifiersISSN: 0142-159X • E-ISSN: 1466-187X
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/0142159x.2026.2653205
PMID41961831
OpenAlexW7153099605
LanguageEN
References cited21

Current medical education is caught in a paradox: it aims to train compassionate patient advocates yet its structure often fosters compliance and burnout, ill-equipping physicians to challenge the systemic drivers of poor health. The rapid integration of artificial intelligence (AI) into clinical practice is automating the cognitive-diagnostic tasks that have long defined physician training, from pattern recognition to data synthesis. This shift presents a specific, time-limited opportunity: rather than simply adopting AI as an efficiency tool within the existing transactional model, medical education can use this moment to fundamentally reimagine the physician's role and the training that shapes it. This requires moving beyond traditional competency-based models to embrace a pedagogy of advocacy, grounded in critical consciousness and systems-level thinking. By transforming curricula to address structural determinants of health, reassessing how we evaluate competence, and creating protected space for advocacy, we can train a new generation of physicians prepared not only to treat disease but to partner in transforming the systems that perpetuate it, through a phased approach aligned with AI maturity in clinical practice

Continuing medical education · Curriculum · Graduate medical education · MEDLINE · Artificial Intelligence in Healthcare and Education · Clinical Reasoning and Diagnostic Skills · Educational Leadership and Innovation

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Citation velocityhistorical
Highly citedNo

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Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae