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

Machine Learning (1973) Coronary Heart Disease (104) Decision Support for Health Professionals (1471) Cardiac Risk and Cardiac Risk Calculators (92) Cardiovascular Disease Prevention (192) Precision Medicine (143)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/74415, first published .
Machine Learning–Based Analysis of Lifestyle Risk Factors for Atherosclerotic Cardiovascular Disease: Retrospective Case-Control Study

Machine Learning–Based Analysis of Lifestyle Risk Factors for Atherosclerotic Cardiovascular Disease: Retrospective Case-Control Study

Machine Learning–Based Analysis of Lifestyle Risk Factors for Atherosclerotic Cardiovascular Disease: Retrospective Case-Control Study

Authors of this article:

Hye-Jin Kim1 Author Orcid Image ;   Heeji Choi1 Author Orcid Image ;   Hyo-Jung Ahn2 Author Orcid Image ;   Seung-Ho Shin1 Author Orcid Image ;   Chulho Kim3 Author Orcid Image ;   Sang-Hwa Lee3 Author Orcid Image ;   Jong-Hee Sohn3 Author Orcid Image ;   Jae-Jun Lee4 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Hye-Jin Kim   1 , PhD ;   Heeji Choi   1 , MSc ;   Hyo-Jung Ahn   2 , MSc ;   Seung-Ho Shin   1 , PhD ;   Chulho Kim   3 , MD, PhD ;   Sang-Hwa Lee   3 , MD, PhD ;   Jong-Hee Sohn   3 , MD, PhD ;   Jae-Jun Lee   4 , MD, PhD

1 Artificial Intelligence Research Center, College of Medicine, Hallym University, Chuhcneon-si, Republic of Korea

2 Health Insurance Review and Assessment Research Institute, Health Insurance Review and Assessment Service, Wonju-si, Republic of Korea

3 Department of Neurology, College of Medicine, Hallym University, Chuncheon-si, Republic of Korea

4 Department of Anesthesiology, College of Medicine, Hallym University, Chuncheon-si, Republic of Korea

Corresponding Author:

  • Chulho Kim, MD, PhD
  • Department of Neurology, College of Medicine
  • Hallym University
  • 1, Hallymdaehak-gil
  • Chuncheon-si 24252
  • Republic of Korea
  • Phone: 82 332405255
  • Fax: 82 1095173201
  • Email: gumdol52@naver.com