Table 4. Performance of the machine-learning algorithms.

Model	F1 score	Accuracy	Precision	Recall	AUC
Random forest (RF)	0.5787 (+/− 0.1283)	0.7836 (+/− 0.0363)	0.6824 (+/− 0.1007)	0.5904 (+/− 0.1452)	0.8505 (+/− 0.1062)
Logistic regression (LR)	0.5730 (+/− 0.1100)	0.7589 (+/− 0.0910)	0.6419 (+/− 0.1221)	0.5848 (+/− 0.1189)	0.7546 (+/− 0.0559)
Support vector machine (SVM)	0.4630 (+/− 0.0587)	0.7726 (+/− 0.0372)	0.4549 (+/− 0.1531)	0.5065 (+/− 0.0162)	0.7879 (+/− 0.0822)