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

Generative Language Models Including ChatGPT (587) Artificial Intelligence (1896) Chatbots and Conversational Agents (678)

Published on in Vol 26 (2024)

This is a member publication of National University of Singapore

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/56413, first published .
Performance of Large Language Models in Patient Complaint Resolution: Web-Based Cross-Sectional Survey

Performance of Large Language Models in Patient Complaint Resolution: Web-Based Cross-Sectional Survey

Performance of Large Language Models in Patient Complaint Resolution: Web-Based Cross-Sectional Survey

Authors of this article:

Lorraine Pei Xian Yong1, 2, 3 Author Orcid Image ;   Joshua Yi Min Tung4 Author Orcid Image ;   Zi Yao Lee1, 2, 3 Author Orcid Image ;   Win Sen Kuan1, 2, 3 Author Orcid Image ;   Mui Teng Chua1, 2, 3 Author Orcid Image
Article Authors Cited by (4) Tweetations (1) Metrics

Journals

  1. Wei B, Hu X, Wu X. Considerations and Challenges in the Application of Large Language Models for Patient Complaint Resolution. Journal of Medical Internet Research 2024;26:e65527 View
  2. Meyer N, Meyer J. A Practical Guide to the Utilization of ChatGPT in the Emergency Department: A Systematic Review of Current Applications, Future Directions, and Limitations. Cureus 2025 View
  3. Fan C, Wang Y, Chen J, Wei Q, Hu S, Xia L, Huang J, Liang W, Wu L, Li X. Early diagnosis and survival outcomes in silicosis: a retrospective cohort study of 11,809 patients in Guangdong Province, China (1956–2020). Frontiers in Public Health 2025;13 View
  4. Gurbuz S, Bahar H, Yavuz U, Keskin A, Karslioglu B, Solak Y. Comparative Efficacy of ChatGPT and DeepSeek in Addressing Patient Queries on Gonarthrosis and Total Knee Arthroplasty. Arthroplasty Today 2025;33:101730 View