Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/76215, first published .
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

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

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