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

AI Language Models in Health Care (661) Cardiac Disease Management (181) Patient Education in Cardiology (59) Design and Evaluation of Patient Education Materials (162) Generative Language Models Including ChatGPT (1375)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/81422, first published .
Doctor analyzing heart health data on a tablet, showing ECG and vital signs.

Large Language Models in Patient Health Communication for Atherosclerotic Cardiovascular Disease: Pilot Cross-Sectional Comparative Analysis

Large Language Models in Patient Health Communication for Atherosclerotic Cardiovascular Disease: Pilot Cross-Sectional Comparative Analysis

Authors of this article:

Pengfei Li1 Author Orcid Image ;   Yinfei Xu1 Author Orcid Image ;   Xiang Liu2 Author Orcid Image ;   Zhean Shen1 Author Orcid Image ;   Yi Wang1 Author Orcid Image ;   Xinyi Lv1 Author Orcid Image ;   Ziyi Lu1 Author Orcid Image ;   Hui Wu1 Author Orcid Image ;   Jiaqi Zhuang1 Author Orcid Image ;   Yan Chen1, 3, 4 Author Orcid Image
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Journals

  1. Cao J, Wang R, Zhao X, Su H. Performance of large language models in patient-facing counseling for atrial fibrillation. Asian Journal of Surgery 2026 View
  2. Zhao Y, Miao Y, Luo Y, Guo R, Wang H, Wu Y. Safety guardrails in patient-facing large language model systems for chronic disease self-management: a realist review. International Journal of Medical Informatics 2026;218:106513 View
  3. Deng B, Wang Z, Cheng T, Zhang Z, Li M. Cross-platform evaluation of LLM-generated educational texts on cardiac myxoma: quality, readability, and actionability using network analysis and latent profile analysis. Frontiers in Cardiovascular Medicine 2026;13 View