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Comment on "Performance and Reproducibility of Large Language Models in Named Entity Recognition: Considerations for the Use in Controlled Environments".

作者信息

Tiffet Théophile, Beltramin Diva, Trombert-Paviot Béatrice, Bousquet Cédric

机构信息

Public Health and Medical Information Unit, University Hospital of Saint-Étienne, Avenue Albert Raimond, 42270, Saint-Priest-en-Jarez, France.

Laboratoire Inserm, SAINBIOSE, U1059, Dysfonction Vasculaire et Hémostase, University Jean-Monnet, 42000, Saint-Étienne, France.

出版信息

Drug Saf. 2025 Sep 2. doi: 10.1007/s40264-025-01592-z.

DOI:10.1007/s40264-025-01592-z
PMID:40892375
Abstract
摘要

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本文引用的文献

[1]
Revolutionizing Health Care: The Transformative Impact of Large Language Models in Medicine.

J Med Internet Res. 2025-1-7

[2]
Performance and Reproducibility of Large Language Models in Named Entity Recognition: Considerations for the Use in Controlled Environments.

Drug Saf. 2025-3

[3]
Challenges and barriers of using large language models (LLM) such as ChatGPT for diagnostic medicine with a focus on digital pathology - a recent scoping review.

Diagn Pathol. 2024-2-27

[4]
The imperative for regulatory oversight of large language models (or generative AI) in healthcare.

NPJ Digit Med. 2023-7-6

[5]
The Role of ChatGPT, Generative Language Models, and Artificial Intelligence in Medical Education: A Conversation With ChatGPT and a Call for Papers.

JMIR Med Educ. 2023-3-6

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