Table 5.

The performance of different machine learning and DL models for hospitalization prediction using the heart datasets

Prediction window	Algorithm	Precision	Recall	F-Measure	AUROC	AUPRC
1y	Logistic	0.777	0.75	0.76	0.695	0.774
	MLP	0.705	0.656	0.676	0.726	0.833
	SMO.PolyKernel	0.688	0.688	0.688	0.543	0.674
	RandomForest	0.599	0.719	0.653	0.56	0.71
	DL	0.611	0.781	0.685	0.50	0.50
3y	Logistic	0.588	0.587	0.588	0.597	0.589
	MLP	0.62	0.619	0.619	0.66	0.647
	SMO.PolyKernel	0.64	0.64	0.636	0.633	0.587
	RandomForest	0.607	0.608	0.603	0.673	0.68
	DL	0.505	0.576	0.50	0.593	0.564
5y	Logistic	0.654	0.658	0.654	0.66	0.641
	MLP	0.649	0.648	0.648	0.68	0.675
	SMO.PolyKernel	0.671	0.668	0.646	0.631	0.598
	RandomForest	0.715	0.71	0.696	0.741	0.745
	DL	0.537	0.554	0.499	0.565	0.547