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

Artificial Intelligence (AI) in Medical Education (828) e-Learning and Digital Medical Education (1629) Information Retrieval (496) Artificial Intelligence (4936)

Published on in Vol 12 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/82885, first published .
Man using a laptop displaying a flowchart for AI text analysis, including TF-IDF vectorization.

ChatGPT versus UpToDate in Preclinical Medical Education: Cross-Sectional Analysis Using Term Frequency–Inverse Document Frequency Cosine Similarity

ChatGPT versus UpToDate in Preclinical Medical Education: Cross-Sectional Analysis Using Term Frequency–Inverse Document Frequency Cosine Similarity

Authors of this article:

Shankar S Thiru1 Author Orcid Image ;   Nicholas E Aksu2 Author Orcid Image ;   Matthew Chiang3 Author Orcid Image ;   Daniel O Gallagher4 Author Orcid Image ;   Mary Furlong5 Author Orcid Image ;   Elizabeth R Prevou6 Author Orcid Image ;   Akhil Jay Khanna2 Author Orcid Image
Article Authors Cited by (3) Tweetations (3) Metrics

Journals

  1. Huang T, Feng X, Song Y. MEC-YOLOv8 and Qwen: An Integrated Situational Awareness Framework for Inland Waterway Shipping. IEEE Access 2026;14:80636 View
  2. Wan Salleh W, Abd Rahim N. Artificial Intelligence in Pharmacology Education Across Undergraduate Health Professions Programmes: A Scoping Review. INTERNATIONAL JOURNAL OF CARE SCHOLARS 2026;9(3):145 View
  3. Tang Z, Song S, Chen X, Qin J, Li Y, Yu J, Yu C, Liu H, Tao X. Artificial intelligence readiness and its association with artificial intelligence literacy among Chinese medical students: a latent profile analysis. Frontiers in Public Health 2026;14 View