A systematic review of large language models and their implications in medical education

In the past year, the use of large language models (LLMs) has generated significant interest and excitement because of their potential to revolutionise various fields, including medical education for aspiring physicians. Although medical students undergo a demanding educational process to become competent health care professionals, the emergence of LLMs presents a promising solution to challenges like information overload, time constraints and pressure on clinical educators. However, integrating LLMs into medical education raises critical concerns and challenges for educators, professionals and students. This systematic review aims to explore LLM applications in medical education, specifically their impact on medical students' learning experiences.

A systematic search was performed in PubMed, Web of Science and Embase for articles discussing the applications of LLMs in medical education using selected keywords related to LLMs and medical education, from the time of ChatGPT's debut until February 2024. Only articles available in full text or English were reviewed. The credibility of each study was critically appraised by two independent reviewers.