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Digital Health Reviews (1884) Machine Learning (2328) Stroke (281) Coronary Heart Disease (119) Myocardial Infarction (Heart Attack) (62) Cardiac Risk and Cardiac Risk Calculators (126) Artificial Intelligence (2482) Applications of AI (394)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/76215, first published .
Man working on a computer displaying a prediction model flowchart and machine learning accuracy graph.

Comparing the Performance of Machine Learning Models and Conventional Risk Scores for Predicting Major Adverse Cardiovascular Cerebrovascular Events After Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction: Systematic Review and Meta-Analysis

Comparing the Performance of Machine Learning Models and Conventional Risk Scores for Predicting Major Adverse Cardiovascular Cerebrovascular Events After Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction: Systematic Review and Meta-Analysis

Authors of this article:

Min-Young Yu1 Author Orcid Image ;   Hae Young Yoo2 Author Orcid Image ;   Ga In Han1 Author Orcid Image ;   Eun-Jung Kim1 Author Orcid Image ;   Youn-Jung Son2 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Min-Young Yu   1 * , MSN ;   Hae Young Yoo   2 * , PhD ;   Ga In Han   1 , MS ;   Eun-Jung Kim   1 , MSN ;   Youn-Jung Son   2 , PhD

1 Graduate School of Nursing, Chung-Ang University, Seoul, Republic of Korea

2 Red-Cross College of Nursing, Chung-Ang University, Seoul, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Youn-Jung Son, PhD
  • Red-Cross College of Nursing, Chung-Ang University
  • 84 Heukseokro, Dongjak gu
  • Seoul 06974
  • Republic of Korea
  • Phone: 82 2-820-5198
  • Email: yjson@cau.ac.kr