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

Digital Health Reviews (1762) Artificial Intelligence (2206) Clinical Informatics (1358) Natural Language Processing (932) mHealth in a Clinical Setting (751)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/84120, first published .
Knowledge-Practice Performance Gap in Clinical Large Language Models: Systematic Review of 39 Benchmarks

Knowledge-Practice Performance Gap in Clinical Large Language Models: Systematic Review of 39 Benchmarks

Knowledge-Practice Performance Gap in Clinical Large Language Models: Systematic Review of 39 Benchmarks

Authors of this article:

Eun Jeong Gong1, 2, 3 Author Orcid Image ;   Chang Seok Bang1, 2, 3 Author Orcid Image ;   Jae Jun Lee3, 4 Author Orcid Image ;   Gwang Ho Baik1, 2 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Lin X, Yang Y, Ren Y. Making Chatbots more human: deep reasoning large language models in ophthalmology. Frontiers in Medicine 2026;12 View