OSCEai dermatology: augmenting dermatologic medical education with Large Language Model GPT-4
DOI:
https://doi.org/10.36834/cmej.80056Abstract
Implication Statement
OSCEai Dermatology demonstrates how large language models (LLMs) like GPT-4 can be integrated into medical education to enhance trainees’ history taking and management skills in an OSCE-like format, including in visual-based specialties like dermatology. By generating diverse, realistic skin cancer role-play scenarios across different skin tones alongside the integration of pre-existing, evidence-based images, the app provides learners with valuable, personalized feedback. This innovation offers a novel, interactive learning tool that supplements traditional teaching methods and can be applied across various specialties. Institutions can adopt or adapt similar LLM-driven educational tools to introduce trainees to a wider range of clinical cases, fostering improved diagnostic skills and patient-centred, culturally sensitive care.
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1. Abd-Alrazaq A, AlSaad R, Alhuwail D, et al. Large Language Models in medical education: opportunities, challenges, and future directions. JMIR Med Educ. 2023 Jun 1;9:e48291. http://dx.doi.org/10.2196/48291.
2. Zhang W, Zeng W, Jiang A, et al. Global, regional and national incidence, mortality and disability-adjusted life-years of skin cancers and trend analysis from 1990 to 2019: an analysis of the Global Burden of Disease Study 2019. Cancer Med. 2021 Jul;10(14):4905–22. http://dx.doi.org/10.1002/cam4.4046
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Copyright (c) 2025 Ye-Jean Park, Eddie Guo, Muskaan Sachdeva, Bryan Ma, Sara Mirali, Brian Rankin, Nikki Nathanielsz, Abrahim Abduelmula, Tatiana Lapa, Mehul Gupta, Trevor Champagne
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