Impact of Large Language Models on Medical Education and Teaching Adaptations

IF 3.1 3区 医学 Q2 MEDICAL INFORMATICS
Li Zhui, Nina Yhap, Liu Liping, Wang Zhengjie, Xiong Zhonghao, Yuan Xiaoshu, Cui Hong, Liu Xuexiu, Ren Wei
{"title":"Impact of Large Language Models on Medical Education and Teaching Adaptations","authors":"Li Zhui, Nina Yhap, Liu Liping, Wang Zhengjie, Xiong Zhonghao, Yuan Xiaoshu, Cui Hong, Liu Xuexiu, Ren Wei","doi":"10.2196/55933","DOIUrl":null,"url":null,"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.","PeriodicalId":56334,"journal":{"name":"JMIR Medical Informatics","volume":"66 1","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR Medical Informatics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2196/55933","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL INFORMATICS","Score":null,"Total":0}
引用次数: 0

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.
大语言模型对医学教育和教学调整的影响
这篇观点文章探讨了 Chat Generative Pre-trained Transformer(ChatGPT)对医学教育的变革性影响,强调了其机遇和挑战。ChatGPT 是 OpenAI 的产品,利用先进的深度学习模型提供多样化的应用,包括提高教学效率、促进个性化学习、强化临床技能培训、改进医学教学评估、提高医学研究效率以及支持继续医学教育。虽然 ChatGPT 在医学教育中的应用前景广阔,但也引发了人们对响应准确性、过度依赖、缺乏情商以及隐私和数据安全风险等问题的担忧。文章强调了认真应对这些挑战的迫切需要,概述了提高医疗信息准确性、加强隐私和数据安全以及促进 ChatGPT 和其他人工智能技术在医学教育中的协同作用的未来途径。报告强调了在医学教育中广泛整合 ChatGPT 的过程中教育工作者的适应性和变革意义。教育者必须始终坚持发挥领导作用,指导学生以合乎道德的方式有效使用 ChatGPT,培养学生的独立思考能力和批判性推理能力。在这个充满活力的技术时代,保障医学教育的质量和完整性仍然至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
JMIR Medical Informatics
JMIR Medical Informatics Medicine-Health Informatics
CiteScore
7.90
自引率
3.10%
发文量
173
审稿时长
12 weeks
期刊介绍: JMIR Medical Informatics (JMI, ISSN 2291-9694) is a top-rated, tier A journal which focuses on clinical informatics, big data in health and health care, decision support for health professionals, electronic health records, ehealth infrastructures and implementation. It has a focus on applied, translational research, with a broad readership including clinicians, CIOs, engineers, industry and health informatics professionals. Published by JMIR Publications, publisher of the Journal of Medical Internet Research (JMIR), the leading eHealth/mHealth journal (Impact Factor 2016: 5.175), JMIR Med Inform has a slightly different scope (emphasizing more on applications for clinicians and health professionals rather than consumers/citizens, which is the focus of JMIR), publishes even faster, and also allows papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信