Predicting 30-day mortality after ST elevation myocardial infarction: Machine learning- based random forest and its external validation using two independent nationwide datasets

CONCLUSIONS: The random forest predictive model for 30-day mortality post STEMI, developed on the ACSIS national registry, has been validated in the MINAP large external cohort and can be applied early at admission for risk stratification. The model performed better than the commonly used GRACE score. Furthermore, to the best of our knowledge, this is the first externally validated ML-based model for STEMI.PMID:34154875 | DOI:10.1016/j.jjcc.2021.06.002

Source: Journal of Cardiology - June 22, 2021 Category: Cardiology Authors: Amir Hadanny Roni Shouval Jianhua Wu Nir Shlomo Ron Unger Doron Zahger Shlomi Matetzky Ilan Goldenberg Roy Beigel Chris Gale Zaza Iakobishvili Source Type: research