Table 2.

Performance of each model for prediction.

Model	AUCa (%)	Sensitivity (%)	F1 score	Accuracy (%)	PPVb	NPVc
XGBoost	0.824	0.595	0.407	0.826	0.307	0.950
LRd	0.800	0.607	0.413	0.827	0.311	0.951
RFe	0.779	0.571	0.392	0.823	0.298	0.947
SVMf	0.701	0.345	0.258	0.801	0.204	0.921

^aAUC: area under the curve.

^bPPV: positive predictive value.

^cNPV: negative predictive value.

^dLR: logistic regression.

^eRF: random forest.

^fSVM: support vector machine.