Table 4.

Performance of models.

Method	Cut-off value	Sensitivity	Specificity	PPV	NPV	AUC
LR	0.019	0.58	0.49	0.02	0.98	0.521 ± 0.028
RF	0.056	0.71	0.92	0.15	0.99	0.911 ± 0.015
SVM	0.016	0.87	0.64	0.05	1	0.863 ± 0.022
XGBoost	0.03	0.84	0.89	0.13	0.996	0.924 ± 0.013
ET	0.044	0.77	0.9	0.13	0.995	0.904 ± 0.014

LR, Logistic regression; RF, Random Forest; SVM, Support Vector Machines; ET, ExtraTree.