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

Digital Health Reviews (1724) Artificial Intelligence (2129) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (87) Machine Learning (2076) AI Language Models in Health Care (202) Generative Language Models Including ChatGPT (708) Clinical Information and Decision Making (1915)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71916, first published .
Implementing Large Language Models in Health Care: Clinician-Focused Review With Interactive Guideline

Implementing Large Language Models in Health Care: Clinician-Focused Review With Interactive Guideline

Implementing Large Language Models in Health Care: Clinician-Focused Review With Interactive Guideline

Authors of this article:

HongYi Li1, 2 Author Orcid Image ;   Jun-Fen Fu3, 4, 5 Author Orcid Image ;   Andre Python1, 6, 7 Author Orcid Image
Article Authors Cited by (5) Tweetations (1) Metrics

Journals

  1. Komasawa N. Generative AI in perioperative medicine and anesthesiology: ethical integration, educational innovation, and the future of clinical professionalism. Journal of Anesthesia 2025 View
  2. Liu J, Liu F, Wang C, Liu S. Prompt Engineering in Clinical Practice: Tutorial for Clinicians. Journal of Medical Internet Research 2025;27:e72644 View
  3. Python A, Li H, Fu J. Author's Reply: Critical Limitations in Systematic Reviews of Large Language Models in Health Care. Journal of Medical Internet Research 2025;27:e82729 View
  4. Weizman Z. Critical Limitations in Systematic Reviews of Large Language Models in Health Care. Journal of Medical Internet Research 2025;27:e81769 View
  5. Zhang Z, Zhang H, Pan Z, Bi Z, Wan Y, Song X, Fan X. Evaluating Large Language Models in Ophthalmology: Systematic Review. Journal of Medical Internet Research 2025;27:e76947 View