Risk Prediction of Major Adverse Cardiovascular Events Within One Year After Percutaneous Coronary Intervention in Patients With Acute Coronary Syndrome: Machine Learning–Based Time-to-Event Analysis

Journals

1. Geremew G, Bekalu A, Tadesse G, Fentahun S, Zeleke T, Bayleyegn Z, Chanie G, Anberbr S, Ayele H, Mengesha A, Getachew D, Abate L, Beyena A, Legesse Y, Atomsa G, Beshada M, Abebe T, Alemayehu T. Survival and predictors of major adverse cardiovascular events among patients with acute coronary syndrome in Ethiopia: a retrospective cohort study. BMJ Open 2026;16(7):e116166 View
2. Song Q, Li Y, Duan H, Li H, Lin Q, Li D, Wei W, Han D, Zeng M. Machine Learning Based on Multiparametric Features from Dual-Layer Detector Spectral CT for Identifying Ulcer-Like Projection in Aortic Intramural Hematoma. Journal of Imaging Informatics in Medicine 2026 View
3. Mirzohreh S, Roshanravan N, Suleymanov T, Makarov D, Zargarzadeh A, Javanshir E, Separham A, Ghaffari A, Motlagh P, Ghaffari S, Jouyban A. Missing-data–aware machine learning prediction of in-hospital major adverse cardiovascular events after primary percutaneous coronary intervention for ST-segment elevation myocardial infarction. Scientific Reports 2026;16(1) View