JMIR Medical Education | How does ChatGPT perform on the USMLE?
Channel: JMIR Publications
Date: 2023-03-29

In this video, Gunther Eysenbach, chief executive officer of JMIR Publications and executive editor of the Journal of Medical Internet Research, interviews Dr Andrew Taylor from Yale University School of Medicine on their recent publication highlighting the potential of ChatGPT in medical education. Dr Talyor and colleagues examined how the AI model ChatGPT fared on the United States Medical Licensing Examination (USMLE)—read their full paper published in JMIR Medical Education (https://doi.org/10.2196/45312).

In their study, Dr Taylor and colleagues compared ChatGPT to other large language models, such as InstructGPT and GPT-3, and found that ChatGPT's additional dialogic component, driven by prior training on question answering data sets, resulted in additional information and reasoning for the answers it generated. They used several data sets reflective of questions on the USMLE and found that ChatGPT's accuracy in answering those questions was at par with a third-year medical student.

In the interview, Dr Taylor discusses the potential for ChatGPT to be used as an AI-based tutor system or peer buddy for educational purposes, as well as ChatGPT’s limitations, such as the need for structured prompts. Read Dr Gunther Eysenbach’s editorial for an interesting conversation with ChatGPT on this topic.

Watch this video interview to know more about ChatGPT's potential use in medical education and how it could revolutionize the way we learn and prepare for exams.

Submit your research on the role of generative language models and AI in medical education to JMIR Publications: https://mededu.jmir.org/announcements/365

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DOI - https://doi.org/10.2196/45312
Full-text - https://mededu.jmir.org/2023/1/e45312
Corresponding author - David Chartash, PhD, Section for Biomedical Informatics and Data Science, Yale University School of Medicine, 300 George Street, Suite 50, New Haven, CT, US
Phone - 1 203-737-5379
Email - david.chartash@yale.edu

Keywords - natural language processing, NLP, MedQA, generative pre-trained transformer, GPT, medical education, chatbot, artificial intelligence, education technology, ChatGPT, conversational agent, machine learning

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