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

Reviews in Medical Informatics (455) Clinical Information and Decision Making (3538) Decision Support for Health Professionals (2121) Methods and Instruments in Medical Informatics (397) Machine Learning (3052) Artificial Intelligence (4542) Intensive Care Unit (ICU) (183) Artificial Intelligence (AI) in Medical Education (669) Generative Language Models Including ChatGPT (1419)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/76326, first published .
Nurse uses tablet with AI brain overlay in ICU, patient on ventilator

Large Language Models in Critical Care Medicine: Scoping Review

Large Language Models in Critical Care Medicine: Scoping Review

Authors of this article:

Tongyue Shi1, 2, 3, 4 Author Orcid Image ;   Jun Ma5 Author Orcid Image ;   Zihan Yu6 Author Orcid Image ;   Haowei Xu1, 4 Author Orcid Image ;   Rongxin Yang1, 2, 3, 4 Author Orcid Image ;   Minqi Xiong7 Author Orcid Image ;   Meirong Xiao1, 2, 3, 4 Author Orcid Image ;   Yilin Li8 Author Orcid Image ;   Huiying Zhao9 Author Orcid Image ;   Guilan Kong1, 2, 3, 4 Author Orcid Image
Article Authors Cited by (8) Tweetations Metrics

Journals

  1. Bignami E, Russo M. From promising prototypes to “instructions for use”: embedding LLMs safely in perioperative and intensive care. Journal of Clinical Monitoring and Computing 2026;40(2):301 View
  2. Subramaniam A, Wong J, Ku D, Carr C, Gupta S, Ku S, Kuroda Y, Yunos N, Nhan L, Pradian E, Rimal A, Rungruanghiranya S, Ryu H, Sainbayar A, See K, Woon C, Hong S. Building your future ICU in Asia Pacific: A structured regional priority-mapping summit report from the Asia Pacific Critical Care Societies Summit 2025. Journal of Critical Care 2026;94:155529 View
  3. Yeh Y, Shih M, De Backer D, Celi L, See K, Fujii T, Ling L, Mongkolpun W, Hu H, Chen H, Chen W, Cholley B, Fong K, Ryu H, Na S, Egi M, Chan W, Chen K, Kamaleswaran R, Chuang Y, Yang C, Hsiao W, Lai S, Ku D, Jahan A, Martin G. The IMPACT framework for evaluating generative AI in critical care: development and multinational consensus validation. Annals of Intensive Care 2026;16:100078 View
  4. Workum J, Jung C, Beil M. Generative artificial intelligence for outcome prediction in critical care: the future is now?. Current Opinion in Critical Care 2026 View
  5. AMRIN S, SATBAYEVA A, ABDUSSEMYATOVA A, DUISEN Y. DIAGNOSTIC ACCURACY AND THERAPEUTIC RATIONALITY IN ACID-BASE IMBALANCES: A COMPARATIVE ANALYSIS BETWEEN PHYSICIANS AND ARTIFICIAL INTELLIGENCE. Vestnik 2026;(2(77)):68 View
  6. Hu S, Lin B, Lin F. Evaluation of large language model–generated information in diabetes health patient education: a scoping review. Frontiers in Public Health 2026;14 View
  7. Zhou Y, Xiong W, Liu H, Wang Q, Luo H, Yang Y, Liu S, Long Y. The “DeepSeek effect” and the adoption–integration gap of generative artificial intelligence in clinical practice: a national online convenience cross-sectional survey of academic critical care physicians in China. Frontiers in Medicine 2026;13 View
  8. Geng W, Liu D, Li L, Wang Y. Evaluating Large Language Models as Post Hoc Explainability Interfaces for Credit Risk Models. Expert Systems 2026;43(8) View