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

Artificial Intelligence (1773) Machine Learning (1769) Cardiology (202) Hypertension Prevention and Treatment (264) Cardiac Risk and Cardiac Risk Calculators (72) Advanced Data Analytics in eHealth (169) Clinical Information and Decision Making (1686) Decision Support for Health Professionals (1360)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52794, first published .
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

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

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

Authors of this article:

Seung Ha Hwang1, 2 Author Orcid Image ;   Hayeon Lee1, 2 Author Orcid Image ;   Jun Hyuk Lee3 Author Orcid Image ;   Myeongcheol Lee2, 4 Author Orcid Image ;   Ai Koyanagi5 Author Orcid Image ;   Lee Smith6 Author Orcid Image ;   Sang Youl Rhee2, 4, 7 Author Orcid Image ;   Dong Keon Yon2, 4, 8 Author Orcid Image ;   Jinseok Lee1 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Journals

  1. Kim S, Kim H, Kim S, Lee H, Hammoodi A, Choi Y, Kim H, Smith L, Kim M, Fond G, Boyer L, Baik S, Lee H, Park J, Kwon R, Woo S, Yon D. Machine Learning–Based Prediction of Substance Use in Adolescents in Three Independent Worldwide Cohorts: Algorithm Development and Validation Study. Journal of Medical Internet Research 2025;27:e62805 View
  2. Choi Y, Park J, Kim H, Lee Y, Lee Y, Choi Y, Yeo S, Kang J, Rahmati M, Lee H, Yon D, Lee J. Artificial intelligence models predicting abnormal uterine bleeding after COVID-19 vaccination. Scientific Reports 2025;15(1) View