Table 2.

The AUC of ML models and TIMI risk score for in-hospital selected features based on 30% testing dataset.

Predictive models	The area under the ROC Curve (95% CI)
	In-Hospital Selected Features
Logistic Regression	0.834 (0.803–0.865)
SVM (Linear)	0.833 (0.803–0.864)
Random Forest	0.843 (0.813–0.873)
Naïve Bayes	0.838 (0.807–0.869)
XGBoost	0.836 (0.804–0.868)
Stacked EL	0.842 (0.812–0.873)
TIMI (STEMI)	0.791 (0.757–0.825)
TIMI (NSTEMI)	0.565 (0.505–0.625)