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

Artificial Intelligence (2295) Generative Language Models Including ChatGPT (775) AI Language Models in Health Care (230) E-Health Policy and Health Systems Innovation (358) Adoption and Change Management of eHealth Systems (938) Ethical, Legal, and Social Issues in AI (120)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/84918, first published .
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

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
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Journals

  1. Eshun I, Odai R, Alao G. Human-In-The-Loop Large Language Models for Decision Support in Modern Power Systems: Capabilities, Risks, and Governance. Journal of Trending Research 2026;1(1):8 View