Table 4.

The list of the applied ML-algorithms and corresponded quality metrics (confusion matrix, sensitivity, specificity, accuracy, AUC ROC).

ML algorithms	Confusion matrix (TP, FP, FN, TN)		Sensitivity	Specificity	Accuracy	AUC ROC
Logistic regression	28	8	0.82	0.89	0.87	0.94
	6	66
SVM	26	4	0.76	0.96	0.89	0.96
	8	70
Decision trees	24	10	0.71	0.86	0.82	0.86
	10	64
Random forest	26	0	0.76	1.00	0.93	0.98
	8	74
Gradient boosting	23	4	0.67	0.95	0.86	0.93
	11	70