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

Viewpoints and Perspectives (514) Artificial Intelligence (1371) Clinical Information and Decision Making (1407) Decision Support for Health Professionals (1185) Machine Learning (1465) Cardiovascular Disease Prevention (137)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47645, first published .
Pitfalls in Developing Machine Learning Models for Predicting Cardiovascular Diseases: Challenge and Solutions

Pitfalls in Developing Machine Learning Models for Predicting Cardiovascular Diseases: Challenge and Solutions

Pitfalls in Developing Machine Learning Models for Predicting Cardiovascular Diseases: Challenge and Solutions

Authors of this article:

Yu-Qing Cai1 Author Orcid Image ;   Da-Xin Gong2 Author Orcid Image ;   Li-Ying Tang1 Author Orcid Image ;   Yue Cai1 Author Orcid Image ;   Hui-Jun Li3 Author Orcid Image ;   Tian-Ci Jing2 Author Orcid Image ;   Mengchun Gong4 Author Orcid Image ;   Wei Hu5 Author Orcid Image ;   Zhen-Wei Zhang6 Author Orcid Image ;   Xingang Zhang7 Author Orcid Image ;   Guang-Wei Zhang2 Author Orcid Image
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Journals

  1. Hwang S, Lee H, Lee J, Lee M, Koyanagi A, Smith L, Rhee S, Yon D, Lee J. Machine Learning–Based Prediction for Incident Hypertension Based on Regular Health Checkup Data: Derivation and Validation in 2 Independent Nationwide Cohorts in South Korea and Japan. Journal of Medical Internet Research 2024;26:e52794 View