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

Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1803) Peer-to-Peer Support and Online Communities (726) Nephrology/Renal Disorders (83) Artificial Intelligence (1781) Chatbots and Conversational Agents (645) Generative Language Models Including ChatGPT (522)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/66365, first published .
Identifying Kidney Stone Risk Factors Through Patient Experiences With a Large Language Model: Text Analysis and Empirical Study

Identifying Kidney Stone Risk Factors Through Patient Experiences With a Large Language Model: Text Analysis and Empirical Study

Identifying Kidney Stone Risk Factors Through Patient Experiences With a Large Language Model: Text Analysis and Empirical Study

Authors of this article:

Chao Mao1 Author Orcid Image ;   Jiaxuan Li1 Author Orcid Image ;   Patrick Cheong-Iao Pang1 Author Orcid Image ;   Quanjing Zhu2 Author Orcid Image ;   Rong Chen3 Author Orcid Image
Article Authors Cited by (1) Tweetations (1) Metrics

Chao Mao   1 , MSc ;   Jiaxuan Li   1 , MSc ;   Patrick Cheong-Iao Pang   1 , PhD ;   Quanjing Zhu   2 , MSc ;   Rong Chen   3 , MD

1 MPU-UC Joint Research Laboratory in Advanced Technologies for Smart Cities, Faculty of Applied Sciences, Macao Polytechnic University, Macao, Macao

2 Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China

3 Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China

Corresponding Author:

  • Patrick Cheong-Iao Pang, PhD
  • MPU-UC Joint Research Laboratory in Advanced Technologies for Smart Cities
  • Faculty of Applied Sciences
  • Macao Polytechnic University
  • Rua de Luís Gonzaga Gomes
  • Macao 999078
  • Macao
  • Phone: 853 85996886
  • Email: mail@patrickpang.net