Benchmarking large language models for biomedical natural language processing applications and recommendations.

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Title: Benchmarking large language models for biomedical natural language processing applications and recommendations.
Authors: Chen Q; Department of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA.; National Library of Medicine, National Institutes of Health, Bethesda, MD, USA., Hu Y; McWilliams School of Biomedical Informatics, University of Texas Health Science at Houston, Houston, TX, USA., Peng X; Department of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA., Xie Q; Department of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA., Jin Q; National Library of Medicine, National Institutes of Health, Bethesda, MD, USA., Gilson A; Department of Ophthalmology and Visual Science, Yale School of Medicine, Yale University, New Haven, CT, USA., Singer MB; Department of Ophthalmology and Visual Science, Yale School of Medicine, Yale University, New Haven, CT, USA., Ai X; Department of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA., Lai PT; National Library of Medicine, National Institutes of Health, Bethesda, MD, USA., Wang Z; National Library of Medicine, National Institutes of Health, Bethesda, MD, USA., Keloth VK; Department of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA., Raja K; Department of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA., Huang J; Department of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA., He H; Department of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA., Lin F; Department of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA., Du J; McWilliams School of Biomedical Informatics, University of Texas Health Science at Houston, Houston, TX, USA., Zhang R; Division of Computational Health Sciences, Department of Surgery, Medical School, University of Minnesota, Minneapolis, MN, USA.; Center for Learning Health System Sciences, University of Minnesota, Minneapolis, MN, 55455, USA., Zheng WJ; McWilliams School of Biomedical Informatics, University of Texas Health Science at Houston, Houston, TX, USA., Adelman RA; Department of Ophthalmology and Visual Science, Yale School of Medicine, Yale University, New Haven, CT, USA., Lu Z; National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. zhiyong.lu@nih.gov., Xu H; Department of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA. hua.xu@yale.edu.
Source: Nature communications [Nat Commun] 2025 Apr 06; Vol. 16 (1), pp. 3280. Date of Electronic Publication: 2025 Apr 06.
Publication Type: Journal Article
Journal Info: Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2041-1723
DOI:10.1038/s41467-025-56989-2