Table 4.

Effect assessment of machine learning models in the testing set.

Models	Accuracy (%)	Sensitivity (%)	Specificity (%)	PPV (%)	NPV (%)	AUC (95%CI)
C5.0-5	70.10	96.72	25.00	68.60	81.82	0.609 (0.504-0.706)
ANN-5	76.29	78.69	72.22	82.76	66.67	0.755 (0.657-0.836)
SVM-5	68.04	91.80	27.78	68.29	66.67	0.598 (0.493-0.696)
Fisher-5	73.20	78.69	63.89	78.69	63.89	0.713 (0.612-0.800)
C5.0-3	65.98	60.66	75.00	80.43	52.94	0.678 (0.576-0.770)
ANN-3	67.01	67.21	66.67	77.36	54.55	0.669 (0.567-0.762)
SVM-3	60.82	49.18	80.56	81.08	48.33	0.649 (0.545-0.743)
Fisher-3	56.70	40.98	83.33	80.65	45.45	0.622 (0.517-0.718)
C5.0-8	85.57	81.97	91.67	94.34	75.00	0.868 (0.784-0.928)
ANN-8	82.47	77.05	91.67	94.00	70.21	0.844 (0.756-0.909)
SVM-8	68.04	60.66	80.56	84.09	54.72	0.706 (0.605-0.794)
Fisher-8	75.26	70.49	83.33	87.76	62.50	0.769 (0.673-0.849)