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

ABSTRACT:

Background

Kidney stones, a prevalent urinary disease, pose significant health risks. Factors like insufficient water intake or a high-protein diet increase an individual's susceptibility to the disease. Social media platforms can be a valuable avenue for users to share their experiences in managing these risk factors. Analyzing such patient-reported information can provide crucial insights into risk factors, potentially leading to improved quality of life for other patients.

Objective

This study aims to develop a model KSrisk-GPT, based on a large language model (LLM) to identify potential kidney stone risk factors from web-based user experiences.

Methods

This study collected data on the topic of kidney stones on Zhihu in the past 5 years and obtained 11,819 user com

SUBMITTER: Mao C 

PROVIDER: S-EPMC12141965 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature