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An Empirical Evaluation of Prompting Strategies for Large Language Models in Zero-Shot Clinical Natural Language Processing: Algorithm Development and Validation Study.

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第一作者： Sonish,Sivarajkumar

第一单位： Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, United States.

作者： Sonish,Sivarajkumar ^[1] ; Mark,Kelley ^[2] ; Alyssa,Samolyk-Mazzanti ^[2] ; Shyam,Visweswaran ^[3] ; Yanshan,Wang ^[4]

作者单位： Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, United States. ^[1] Department of Health Information Management, University of Pittsburgh, Pittsburgh, PA, United States. ^[2] Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, United States.;Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, United States. ^[3] Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, United States.;Department of Health Information Management, University of Pittsburgh, Pittsburgh, PA, United States.;Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, United States. ^[4]

DOI 10.2196/55318

PMID 38587879

发布时间 2024-04-26

基金项目

R01 LM014306/LM/NLM NIH HHS/United States U24 TR004111/TR/NCATS NIH HHS/United States

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An Empirical Evaluation of Prompting Strategies for Large Language Models in Zero-Shot Clinical Natural Language Processing: Algorithm Development and Validation Study.

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An Empirical Evaluation of Prompting Strategies for Large Language Models in Zero-Shot Clinical Natural Language Processing: Algorithm Development and Validation Study.

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