OSCEai dermatology: augmenting dermatologic medical education with Large Language Model GPT-4

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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Publication Details

Journal
Canadian Medical Education Journal
Published
2025-08-08
DOI
https://doi.org/10.36834/cmej.80056
Citations
2
Primary Topic
Medicine and Dermatology Studies History
Type
article
Field-Weighted Citation Impact
4.01
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article

OSCEai dermatology: augmenting dermatologic medical education with Large Language Model GPT-4

Abrahim Abduelmula, Sara Mirali, Trevor Champagne, Nikki Nathanielsz et al.
2 citations
Canadian Medical Education Journal
Medicine and Dermatology Studies History
4.01
article

OSCEai dermatology: augmenting dermatologic medical education with Large Language Model GPT-4

Abrahim Abduelmula, Sara Mirali, Trevor Champagne, Nikki Nathanielsz, Tatiana Lapa, Muskaan Sachdeva, Eddie Guo, Ye‐Jean Park, Brian D. Rankin, Bryan Ma, Purnima Gupta
article en
2 citations

Abstract

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.

Canadian Medical Education JournalVol. 16(6)
University of Calgary (CA), University of Toronto (CA)
Openalex Percentile: Top 6%
Medicine and Dermatology Studies History
4.01
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OSCEai dermatology: augmenting dermatologic medical education with Large Language Model GPT-4 — Abrahim Abduelmula, Sara Mirali, et al. · Canadian Medical Education Journal (2025) | TGRS Research Map | TGRS