Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/56655, first published .
Quality of Answers of Generative Large Language Models Versus Peer Users for Interpreting Laboratory Test Results for Lay Patients: Evaluation Study

Quality of Answers of Generative Large Language Models Versus Peer Users for Interpreting Laboratory Test Results for Lay Patients: Evaluation Study

Quality of Answers of Generative Large Language Models Versus Peer Users for Interpreting Laboratory Test Results for Lay Patients: Evaluation Study

Journals

  1. Liu M, Okuhara T, Chang X, Shirabe R, Nishiie Y, Okada H, Kiuchi T. Performance of ChatGPT Across Different Versions in Medical Licensing Examinations Worldwide: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2024;26:e60807 View
  2. 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
  3. McDarby M, Mroz E, Hahne J, Malling C, Carpenter B, Parker P. “Hospice Care Could Be a Compassionate Choice”: ChatGPT Responses to Questions About Decision Making in Advanced Cancer. Journal of Palliative Medicine 2024 View
  4. Wu H, Li W, Chen X, Li C. The professionalism of ChatGPT in the field of surgery: low or high level?. International Journal of Surgery 2024;110(9):5859 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