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

Artificial Intelligence (2458) Clinical Informatics (1494) mHealth for Data Collection and Research (1288) Electronic Health Records (1421) Development and Evaluation of Research Methods, Instruments and Tools (855) Systemic Racism and Racial Bias in Health Care and Society (139) Generative Language Models Including ChatGPT (883) Responsible Health AI (105) AI for Synthetic Data (6)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65317, first published .
Doctor typing on laptop with medical history form displayed, blood pressure cuff nearby.

Evaluation and Bias Analysis of Large Language Models in Generating Synthetic Electronic Health Records: Comparative Study

Evaluation and Bias Analysis of Large Language Models in Generating Synthetic Electronic Health Records: Comparative Study

Authors of this article:

Ruochen Huang1 Author Orcid Image ;   Honghan Wu2 Author Orcid Image ;   Yuhan Yuan1 Author Orcid Image ;   Yifan Xu1 Author Orcid Image ;   Hao Qian1 Author Orcid Image ;   Changwei Zhang3, 4 Author Orcid Image ;   Xin Wei4 Author Orcid Image ;   Shan Lu5 Author Orcid Image ;   Xin Zhang5 Author Orcid Image ;   Jingbao Kan5 Author Orcid Image ;   Cheng Wan1 Author Orcid Image ;   Yun Liu5 Author Orcid Image
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Journals

  1. Chen M, Ruan S, Wu J, Chen P. Classifying American Society of Anesthesiologists Physical Status With a Low-Rank–Adapted Large Language Model: Development and Validation Study. Journal of Medical Internet Research 2026;28:e89540 View
  2. Garg M, Raza S, Rayana S, Liu X, Sohn S. The rise of small language models in healthcare: A comprehensive survey. Computer Science Review 2026;62:100999 View

Conference Proceedings

  1. Dildora I, Shokirovich O, Yuldasheva G, Singhal A, Alimardanova R, Abdirahmonov L. 2025 7th International Conference on Information Systems and Computer Networks (ISCON). Democratizing AI Linguistic Technologies for Understanding Diverse Social Voices View