Synthetic medical education in dermatology leveraging generative artificial intelligence.

Journal: NPJ digital medicine
Published Date: May 4, 2025

Abstract

The advent of large language models (LLMs) represents an enormous opportunity to revolutionize medical education. Via "synthetic education," LLMs can be harnessed to generate novel content for medical education purposes, offering potentially unlimited resources for physicians in training. Utilizing OpenAI's GPT-4, we generated clinical vignettes and accompanying explanations for 20 skin and soft tissue diseases tested on the United States Medical Licensing Examination. Physician experts gave the vignettes high average scores on a Likert scale in scientific accuracy (4.45/5), comprehensiveness (4.3/5), and overall quality (4.28/5) and low scores for potential clinical harm (1.6/5) and demographic bias (1.52/5). A strong correlation (r = 0.83) was observed between comprehensiveness and overall quality. Vignettes did not incorporate significant demographic diversity. This study underscores the potential of LLMs in enhancing the scalability, accessibility, and customizability of dermatology education materials. Efforts to increase vignettes' demographic diversity should be incorporated to increase applicability to diverse populations.

Authors

  • Arya S Rao
    Harvard Medical School, Boston, MA, USA.
  • John Kim
    Harvard Medical School, Boston, MA, USA.
  • Andrew Mu
    Harvard Medical School, Boston, MA, USA.
  • Cameron C Young
    Harvard Medical School, Boston, MA, USA.
  • Ezra Kalmowitz
    Harvard Medical School, Boston, MA, USA.
  • Michael Senter-Zapata
    Harvard Medical School, Boston, MA, USA.
  • David C Whitehead
    Harvard Medical School, Boston, MA, USA.
  • Lilit Garibyan
    Harvard Medical School, Boston, MA, USA.
  • Adam B Landman
    Harvard Medical School, Boston, MA, USA.
  • Marc D Succi
    Harvard Medical School, Boston, MA, USA. msucci@mgh.harvard.edu.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals