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

Artificial Intelligence (2202) Generative Language Models Including ChatGPT (745) Foundation Models and Their Applications in AI (52) Demographics of Users, Social & Digital Divide (931) Ethical, Legal, and Social Issues in AI (109)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67383, first published .
Perspectives and Experiences With Large Language Models in Health Care: Survey Study

Perspectives and Experiences With Large Language Models in Health Care: Survey Study

Perspectives and Experiences With Large Language Models in Health Care: Survey Study

Authors of this article:

Jennifer Sumner1 Author Orcid Image ;   Yuchen Wang2 Author Orcid Image ;   Si Ying Tan1 Author Orcid Image ;   Emily Hwee Hoon Chew1 Author Orcid Image ;   Alexander Wenjun Yip1 Author Orcid Image
Article Authors Cited by (4) Tweetations (2) Metrics

Journals

  1. Ralla B, Biernath N, Lichy I, Kurz L, Friedersdorff F, Schlomm T, Schmidt J, Plage H, Jeutner J. How Accurate Is AI? A Critical Evaluation of Commonly Used Large Language Models in Responding to Patient Concerns About Incidental Kidney Tumors. Journal of Clinical Medicine 2025;14(16):5697 View
  2. Teo Z, Thirunavukarasu A, Elangovan K, Cheng H, Moova P, Soetikno B, Nielsen C, Pollreisz A, Ting D, Morris R, Shah N, Langlotz C, Ting D. Generative artificial intelligence in medicine. Nature Medicine 2025;31(10):3270 View
  3. Rokhshad R, Tichy A, Ducret M, Chaurasia A, Uribe S, Gambelin O, Schwendicke F. The ethics and governance of large language models in dentistry: A framework for research and clinical implementation. Journal of Dentistry 2026;164:106187 View
  4. Li P, Xu Y, Liu X, Shen Z, Wang Y, Lv X, Lu Z, Wu H, Zhuang J, Chen Y. Large Language Models in Patient Health Communication for Atherosclerotic Cardiovascular Disease: Pilot Cross-Sectional Comparative Analysis. JMIR Medical Informatics 2026;14:e81422 View