Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Dec 29, 2023
Open Peer Review Period: Dec 29, 2023 - Feb 23, 2024
Date Accepted: Jun 8, 2024
(closed for review but you can still tweet)
Impact of Large Language Models on Medical Education and Teaching Adaptations
ABSTRACT
This viewpoint article explores the transformative impact of Chat Generative Pre-trained Transformer (ChatGPT) on medical education, highlighting its opportunities and challenges. ChatGPT, a product of OpenAI, leverages advanced deep learning models to offer diverse applications, including enhancing teaching efficiency, facilitating personalized learning, reinforcing clinical skills training, improving medical teaching assessment, enhancing efficiency in medical research, and supporting continuing medical education. While presenting promising opportunities, the integration of ChatGPT in medical education raises concerns about response accuracy, overreliance, lack of emotional intelligence, and privacy and data security risks. The article underscores the imperative need to carefully address these challenges, outlining future pathways to bolster medical information accuracy, fortify privacy and data security, and promote synergy between ChatGPT and other artificial intelligence technologies in medical education. It highlights the adaptability and transformative significance of educators amid the widespread integration of ChatGPT in medical education. Educators must consistently uphold a leadership role, guiding students in the ethical and effective use of ChatGPT, nurturing independent thinking, and honing critical reasoning skills. Safeguarding the quality and integrity of medical education in this dynamic technological era remains paramount.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.