Teaching Medicine With Generative Artificial Intelligence (GenAI): A Review of Practices, Pitfalls, and Possibilities in Medical Education
Manuel B. Garcia
a
,
Raquel Simões de Almeida
b
,
Dharel P. Acut
c
,
Rui Pedro Pereira de Almeida
d
,
Precious S. Garcia
e
,
Eleonora Stefani
f
a FEU Institute of Technology, Philippines
b Polytechnic of Porto, Portugal
c Cebu Technological University, Philippines
d University of Algarve, Portugal
e Jose Rizal University, Philippines
f University of Padova, Italy
Abstract: Once confined to science fiction and speculative futures, generative artificial intelligence (GenAI) has swiftly entered the lecture halls of modern medical education. Despite its expanding use, a synthesis of its implementation, limitations, and educational value remains underexplored. This review aims to critically examine current applications, identify pedagogical pitfalls, and delineate future trajectories for GenAI in medical training. Key innovations include AI-driven content generation tailored to curricular benchmarks, automated assessments with real-time diagnostic feedback, and immersive virtual patient simulations replicating complex pathophysiologies. Additional advances span multilingual knowledge translation, anatomically precise surgical training environments, and adaptive learning systems powered by intelligent tutoring frameworks. As discussed herein, GenAI holds transformative potential for advancing clinical competence in an evolving medical landscape—provided its integration is evidence-based, ethically sound, and educationally coherent.