Previously submitted to: Journal of Medical Internet Research (no longer under consideration since Jun 29, 2024)
Date Submitted: Jan 2, 2024
Open Peer Review Period: Jan 9, 2024 - Mar 5, 2024
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The Intent of ChatGPT Usage and its Robustness in Medical Proficiency Exams: A Systematic Review
ABSTRACT
Background:
Since it was first launched, ChatGPT, a Large Language Model, has been widely used across different disciplines, particularly the medical field.
Objective:
The main aim of this review is to thoroughly assess the performance of ChatGPT in subspecialty written medical proficiency exams and comparing its distinct versions
Methods:
Distinct online databases were searched for appropriate articles that fit the intended objectives of the study: PubMed, CINAHL, and Web of Science. A group of reviewers was assembled in order to create an appropriate methodological framework for articles to be included.
Results:
16 articles were adopted for this review that assessed the performance of different ChatGPT versions across different subspecialty written examinations such as surgical subspecialties, and other subspecialties including neurology, orthopedics, trauma and orthopedics, core cardiology, family medicine, and dermatology. The studies reported a distinct accuracy rate, ranging from 35.8% to 91%, across different datasets and subspecialties.
Conclusions:
This review indicates that ChatGPT can be used to enhance learning, provide customized feedback, and support medical students taking a range of medical subspecialty exams. However, to avoid exploitation and any detrimental effects on the real world of medicine, it is crucial to improve the ongoing evaluation of this AI tool.
Citation
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