Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50067, first published .
A Machine Learning Model for Predicting In-Hospital Mortality in Chinese Patients With ST-Segment Elevation Myocardial Infarction: Findings From the China Myocardial Infarction Registry

A Machine Learning Model for Predicting In-Hospital Mortality in Chinese Patients With ST-Segment Elevation Myocardial Infarction: Findings From the China Myocardial Infarction Registry

A Machine Learning Model for Predicting In-Hospital Mortality in Chinese Patients With ST-Segment Elevation Myocardial Infarction: Findings From the China Myocardial Infarction Registry

Journals

  1. Tang N, Liu S, Li K, Zhou Q, Dai Y, Sun H, Zhang Q, Hao J, Qi C. Prediction of in-hospital mortality risk for patients with acute ST-elevation myocardial infarction after primary PCI based on predictors selected by GRACE score and two feature selection methods. Frontiers in Cardiovascular Medicine 2024;11 View
  2. Yang Y, Tang J, Ma L, Wu F, Guan X. A systematic comparison of short-term and long-term mortality prediction in acute myocardial infarction using machine learning models. BMC Medical Informatics and Decision Making 2025;25(1) View
  3. Li W, Lei P, Dong R, He S, Zhang Z, Han B. Machine Learning Approach on Predictive Model Establishment for In-Hospital Mortality in Acute Myocardial Infarction Patients Post-Percutaneous Coronary Intervention: Solutions for Databases With Dimensionality Reduction and Class Imbalance. Reviews in Cardiovascular Medicine 2025;26(9) View
  4. Jian R, Zhang J, Zeng Y, Zhou T, Wu Y, Wu L, Yu Y, Xi C. In-hospital mortality risk prediction models for patients with acute coronary syndrome: a systematic review and meta-analysis. Frontiers in Cardiovascular Medicine 2025;12 View

Books/Policy Documents

  1. Sanyal P, Kuthe M, Maurya S, Partakke S, Ismail F, Garg R. Smart Trends in Computing and Communications. View