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

Public Health for Asian/Pacific Islands (6) Public (e)Health, Digital Epidemiology and Public Health Informatics (725) Longitudinal and Cohort Studies in Public Health (309) Decision Support for Health Professionals (1185) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (36) Machine Learning (49)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48378, first published .
A Random Forest Algorithm for Assessing Risk Factors Associated With Chronic Kidney Disease: Observational Study

A Random Forest Algorithm for Assessing Risk Factors Associated With Chronic Kidney Disease: Observational Study

A Random Forest Algorithm for Assessing Risk Factors Associated With Chronic Kidney Disease: Observational Study

Authors of this article:

Pei Liu1 Author Orcid Image ;   Yijun Liu2 Author Orcid Image ;   Hao Liu3 Author Orcid Image ;   Linping Xiong2 Author Orcid Image ;   Changlin Mei4 Author Orcid Image ;   Lei Yuan2 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Pei Liu   1 * , MSc ;   Yijun Liu   2 * , BS ;   Hao Liu   3 * , MSc ;   Linping Xiong   2 , MD, DSC ;   Changlin Mei   4 , MD ;   Lei Yuan   2 , BS

1 Department of Mathematics and Physics, Second Military Medical University, Shanghai, China

2 Department of Health Management, Second Military Medical University, Shanghai, China

3 Faculty of Health Service, Second Military Medical University, Shanghai, China

4 Nephrology Department, Shanghai Changzheng Hospital, Shanghai, China

*these authors contributed equally

Corresponding Author:

  • Lei Yuan, BS
  • Department of Health Management
  • Second Military Medical University
  • No.800 Xiangyin Road, Yangpu District, Shanghai, China
  • Shanghai, 200433
  • China
  • Phone: 86 15026929271
  • Email: yuanleigz@163.com