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This paper is in the following e-collection/theme issue:

Artificial Intelligence (4438) E-Health Policy and Health Systems Innovation (502) Adoption and Change Management of eHealth Systems (1067) Generative Language Models Including ChatGPT (1370) AI Language Models in Health Care (655) Ethical, Legal, and Social Issues in AI (186)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/84918, first published .
AI chip, caduceus, and handshake symbolizing AI in healthcare

Factors Influencing Adoption of Large Language Models in Health Care: Multicenter Cross-Sectional Mixed Methods Observational Study

Factors Influencing Adoption of Large Language Models in Health Care: Multicenter Cross-Sectional Mixed Methods Observational Study

Authors of this article:

Xiongwen Yang1, 2 Author Orcid Image ;   Yi Xiao3 Author Orcid Image ;   Di Liu1, 2 Author Orcid Image ;   Huiyin Deng4 Author Orcid Image ;   Jian Huang5 Author Orcid Image ;   Yubin Zhou6 Author Orcid Image ;   Maoli Liang2, 7 Author Orcid Image ;   Longyan Dong8 Author Orcid Image ;   Zihao Yuan8 Author Orcid Image ;   Jing Yao1, 2 Author Orcid Image ;   Wankai Guo1, 2 Author Orcid Image ;   Chuan Xu1, 2 Author Orcid Image
Article Authors Cited by (10) Tweetations Metrics Author Video

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  9. Ben Tamo J, Nnamdi M, Marteau B, Wang S, Shi W, Akay Y, Akay M, Wang M. Megatrends in Biomedical AI for Health Care From Data Foundations to Clinical Deployment. Computer 2026;59(6):51 View
  10. Rader B, Nagy R, Nelson H, Laussen P, Brownstein J. Meeting clinicians where they are through signal-guided AI innovation. BMJ Digital Health & AI 2026;2(1):e000064 View