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
Journals
- Fan H, Fu X, Guo Q, Jia F, Wei X, Liu J, Zhang N, Zhu C, Shi J, Zhang L, Li J. Early diagnostic biomarkers for acute myocardial infarction unveiled by metabolomics, Mendelian randomization, and machine learning. Molecular Biomedicine 2026;7(1) View
- Song Y, Cao X, Zhang H, Tian X, Hua H, Ferdous M, Zhang J, Zhao P. Construction of classification model and analysis of risk factors in patients with multi-vessel coronary artery disease. BMC Medical Informatics and Decision Making 2026 View