Table 3.

Multimodel classification—training cohort *.

Classification Model	AUC	Cut-Off	Accuracy	Sensitivity	Specificity	Positive Predictive Value	Negative Predictive Value	F1 Score
Logistic regression	0.846 (0.006)	0.305 (0.016)	0.870 (0.004)	0.761 (0.010)	0.970 (0.005)	0.715 (0.011)	0.921 (0.003)	0.737 (0.008)
SVM	0.730 (0.008)	0.191 (0.100)	0.792 (0.029)	0.646 (0.059)	0.845 (0.054)	0.575 (0.097)	0.879 (0.009)	0.599 (0.018)
KNN	0.845 (0.003)	0.400 (0.001)	0.887 (0.005)	0.931 (0.014)	0.817 (0.012)	0.828 (0.021)	0.901 (0.007)	0.876 (0.012)

* All values are shown as mean (standard deviation). Abbreviations: AUC, Aera Under Curve; SVM, support vector machine; KNN, k-nearest neighbor.