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- Publisher Website: 10.1093/jamia/ocad252
- Scopus: eid_2-s2.0-85185345007
- PMID: 38269644
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Article: Harnessing the potential of large language models in medical education: promise and pitfalls
Title | Harnessing the potential of large language models in medical education: promise and pitfalls |
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Authors | |
Keywords | ChatGPT large language models medical education |
Issue Date | 1-Mar-2024 |
Publisher | Oxford University Press |
Citation | A Scholarly Journal of Informatics in Health and Biomedicine, 2024, v. 31, n. 3, p. 776-783 How to Cite? |
Abstract | Objectives: To provide balanced consideration of the opportunities and challenges associated with integrating Large Language Models (LLMs) throughout the medical school continuum. Process: Narrative review of published literature contextualized by current reports of LLM application in medical education. Conclusions: LLMs like OpenAI's ChatGPT can potentially revolutionize traditional teaching methodologies. LLMs offer several potential advantages to students, including direct access to vast information, facilitation of personalized learning experiences, and enhancement of clinical skills development. For faculty and instructors, LLMs can facilitate innovative approaches to teaching complex medical concepts and fostering student engagement. Notable challenges of LLMs integration include the risk of fostering academic misconduct, inadvertent overreliance on AI, potential dilution of critical thinking skills, concerns regarding the accuracy and reliability of LLM-generated content, and the possible implications on teaching staff. |
Persistent Identifier | http://hdl.handle.net/10722/348260 |
ISSN | 2023 Impact Factor: 4.7 2023 SCImago Journal Rankings: 2.123 |
DC Field | Value | Language |
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dc.contributor.author | Benítez, Trista M. | - |
dc.contributor.author | Xu, Yueyuan | - |
dc.contributor.author | Boudreau, J. Donald | - |
dc.contributor.author | Kow, Alfred Wei Chieh | - |
dc.contributor.author | Bello, Fernando | - |
dc.contributor.author | Phuoc, Le Van | - |
dc.contributor.author | Wang, Xiaofei | - |
dc.contributor.author | Sun, Xiaodong | - |
dc.contributor.author | Leung, Gilberto Ka Kit | - |
dc.contributor.author | Lan, Yanyan | - |
dc.contributor.author | Wang, Yaxing | - |
dc.contributor.author | Cheng, Davy | - |
dc.contributor.author | Tham, Yih Chung | - |
dc.contributor.author | Wong, Tien Yin | - |
dc.contributor.author | Chung, Kevin C | - |
dc.date.accessioned | 2024-10-08T00:31:17Z | - |
dc.date.available | 2024-10-08T00:31:17Z | - |
dc.date.issued | 2024-03-01 | - |
dc.identifier.citation | A Scholarly Journal of Informatics in Health and Biomedicine, 2024, v. 31, n. 3, p. 776-783 | - |
dc.identifier.issn | 1067-5027 | - |
dc.identifier.uri | http://hdl.handle.net/10722/348260 | - |
dc.description.abstract | <p>Objectives: To provide balanced consideration of the opportunities and challenges associated with integrating Large Language Models (LLMs) throughout the medical school continuum. Process: Narrative review of published literature contextualized by current reports of LLM application in medical education. Conclusions: LLMs like OpenAI's ChatGPT can potentially revolutionize traditional teaching methodologies. LLMs offer several potential advantages to students, including direct access to vast information, facilitation of personalized learning experiences, and enhancement of clinical skills development. For faculty and instructors, LLMs can facilitate innovative approaches to teaching complex medical concepts and fostering student engagement. Notable challenges of LLMs integration include the risk of fostering academic misconduct, inadvertent overreliance on AI, potential dilution of critical thinking skills, concerns regarding the accuracy and reliability of LLM-generated content, and the possible implications on teaching staff.</p> | - |
dc.language | eng | - |
dc.publisher | Oxford University Press | - |
dc.relation.ispartof | A Scholarly Journal of Informatics in Health and Biomedicine | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | ChatGPT | - |
dc.subject | large language models | - |
dc.subject | medical education | - |
dc.title | Harnessing the potential of large language models in medical education: promise and pitfalls | - |
dc.type | Article | - |
dc.identifier.doi | 10.1093/jamia/ocad252 | - |
dc.identifier.pmid | 38269644 | - |
dc.identifier.scopus | eid_2-s2.0-85185345007 | - |
dc.identifier.volume | 31 | - |
dc.identifier.issue | 3 | - |
dc.identifier.spage | 776 | - |
dc.identifier.epage | 783 | - |
dc.identifier.eissn | 1527-974X | - |
dc.identifier.issnl | 1067-5027 | - |