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

Machine Learning (1941) Adoption and Change Management of eHealth Systems (861) Advanced Data Analytics in eHealth (190) Big Data (303) Electronic Health Records (1263) Methods and Instruments in Medical Informatics (178) New Technologies (103) Tools, Programs and Algorithms (356) Decision Support for Health Professionals (1458)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64972, first published .
Machine Learning–Based Risk Factor Analysis and Prediction Model Construction for the Occurrence of Chronic Heart Failure: Health Ecologic Study

Machine Learning–Based Risk Factor Analysis and Prediction Model Construction for the Occurrence of Chronic Heart Failure: Health Ecologic Study

Machine Learning–Based Risk Factor Analysis and Prediction Model Construction for the Occurrence of Chronic Heart Failure: Health Ecologic Study

Authors of this article:

Qian Xu1 Author Orcid Image ;   Xue Cai2 Author Orcid Image ;   Ruicong Yu1 Author Orcid Image ;   Yueyue Zheng3 Author Orcid Image ;   Guanjie Chen4 Author Orcid Image ;   Hui Sun1 Author Orcid Image ;   Tianyun Gao1 Author Orcid Image ;   Cuirong Xu5 Author Orcid Image ;   Jing Sun6 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Jin X, Wang Y, Wang J, Gao Q, Huang Y, Shao L, Zhao J, Li J, Li L, Zhang Z, Li S, Liu Y. A Machine Learning Approach to Differentiate Cold and Hot Syndrome in Viral Pneumonia Integrating Traditional Chinese Medicine and Modern Medicine: Machine Learning Model Development and Validation. JMIR Medical Informatics 2025;13:e64725 View