Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55847, first published .
Leveraging Large Language Models for Improved Patient Access and Self-Management: Assessor-Blinded Comparison Between Expert- and AI-Generated Content

Leveraging Large Language Models for Improved Patient Access and Self-Management: Assessor-Blinded Comparison Between Expert- and AI-Generated Content

Leveraging Large Language Models for Improved Patient Access and Self-Management: Assessor-Blinded Comparison Between Expert- and AI-Generated Content

Journals

  1. Yong L, Tung J, Lee Z, Kuan W, Chua M. Performance of Large Language Models in Patient Complaint Resolution: Web-Based Cross-Sectional Survey. Journal of Medical Internet Research 2024;26:e56413 View
  2. Yu H, Fan L, Li L, Zhou J, Ma Z, Xian L, Hua W, He S, Jin M, Zhang Y, Gandhi A, Ma X. Large Language Models in Biomedical and Health Informatics: A Review with Bibliometric Analysis. Journal of Healthcare Informatics Research 2024;8(4):658 View
  3. Hadar-Shoval D, Asraf K, Shinan-Altman S, Elyoseph Z, Levkovich I. Embedded values-like shape ethical reasoning of large language models on primary care ethical dilemmas. Heliyon 2024;10(18):e38056 View
  4. Kim H, Kim G. Can a large language model create acceptable dental board-style examination questions? A cross-sectional prospective study. Journal of Dental Sciences 2024 View
  5. Aydin S, Karabacak M, Vlachos V, Margetis K. Large language models in patient education: a scoping review of applications in medicine. Frontiers in Medicine 2024;11 View
  6. Wang D, Liang J, Ye J, Li J, Li J, Zhang Q, Hu Q, Pan C, Wang D, Liu Z, Shi W, Shi D, Li F, Qu B, Zheng Y. Enhancement of the Performance of Large Language Models in Diabetes Education through Retrieval-Augmented Generation: Comparative Study. Journal of Medical Internet Research 2024;26:e58041 View