Table 5.

Area under the ROC curve for the developed models on validation data.

	LR	RR	LASSO	Elastic net	CT	RF	XGBoost	NN
	0.870 (0.848–0.893)	0.854 (0.831–0.879)	0.857 (0.834–0.881)	0.857 (0.834–0.881)	0.807 (0.780–0.835)	0.860 (0.836–0.884)	0.872 (0.849–0.894)	0.872 (0.849–0.894)
LR		0.359	0.438	0.444	< 0.001	0.042	0.925	0.930
RR			0.011	0.008	0.010	0.760	0.007	0.002
LASSO				0.185	0.007	0.869	0.017	0.007
Elastic net					0.006	0.876	0.018	0.008
CT						< 0.001	< 0.001	< 0.001
RF							0.485	0.490
XGBoost								0.981

LR logistic regression, RR ridge regression, CT classification tree, RF random forest, XGBoost extreme gradient boosting.