The role of large language models in the peer-review process: opportunities and challenges for medical journal reviewers and editors.
The peer review process ensures the integrity of scientific research. This is particularly important in the medical field, where research findings directly impact patient care. However, the rapid growth of publications has strained reviewers, causing delays and potential declines in quality. Generat...
| Publicado en: | Journal of Educational Evaluation for Health Professions Vol. 22; pp. 1 - 9 |
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| Autores principales: | , , |
| Formato: | review tables/charts Journal Article |
| Publicado: |
National Health Personnel Licensing Examination Board
2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=192170939&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 192170939 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 19755937 B0CC jtl: Journal of Educational Evaluation for Health Professions issn: 19755937 maglogo: N pubinfo: dt: 2025 vid: 22 pid: 58691 pub: National Health Personnel Licensing Examination Board artinfo: ui: 192170939 192170939 192170939 10.3352/jeehp.2025.22.4 192170939 ppf: 1 ppct: 8 formats: fmt: @attributes: type: P tig: atl: The role of large language models in the peer-review process: opportunities and challenges for medical journal reviewers and editors. aug: au: Lee, Jisoo Lee, Jieun Yoo, Jeong-Ju affil: Department of Internal Medicine, Soonchunhyang University Bucheon Hospital, Bucheon, Korea sug: subj: Natural Language Processing Peer Review Editors Serial Publications Research, Medical Linguistics Task Performance and Analysis Artificial Intelligence, Generative Feedback Support, Psychosocial Privacy and Confidentiality ab: The peer review process ensures the integrity of scientific research. This is particularly important in the medical field, where research findings directly impact patient care. However, the rapid growth of publications has strained reviewers, causing delays and potential declines in quality. Generative artificial intelligence, especially large language models (LLMs) such as ChatGPT, may assist researchers with efficient, high-quality reviews. This review explores the integration of LLMs into peer review, highlighting their strengths in linguistic tasks and challenges in assessing scientific validity, particularly in clinical medicine. Key points for integration include initial screening, reviewer matching, feedback support, and language review. However, implementing LLMs for these purposes will necessitate addressing biases, privacy concerns, and data confidentiality. We recommend using LLMs as complementary tools under clear guidelines to support, not replace, human expertise in maintaining rigorous peer review standards. pubtype: Academic Journal doctype: review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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