Table 3.

Comparison of diagnostic efficiency of six different machine learning methods.

Methods	AUC	Accuracy	Precision	Recall	F1-Score
Logistic Regression	0.821	0.737	0.733	0.917	0.815
SVM	0.869	0.789	0.750	1.000	0.857
Random Forest	0.714	0.737	0.733	0.917	0.815
Gradient Boosting	0.679	0.737	0.733	0.917	0.815
AdaBoost	0.786	0.684	0.714	0.833	0.769
KNN	0.839	0.789	0.786	0.917	0.769

AUC, Area Under the Curve.