STEMI-OP algorithms

STEMI-OP algorithms improve in-hospital mortality prediction in silico (AUC 92.16% vs 83.48% (GRACE 2.0) and 87.01% (CADILLAC)).

“The CatBoost model with ElasticNet regression for pre-PCI prediction and the Random Forest model with Ridge regression post-PCI prediction demonstrated significantly superior performance compared to traditional risk scores, achieving AUC values of 92.16% and 95.10%, respectively”

In silicofollowing primary PCI

STEMI-OP in-hospital mortality prediction algorithms: Frailty-integrated machine learning in older patients undergoing primary PCI

npj aging·6 Jun 2025