Table 3.

Performance comparison of different ML models on the evaluation dataset.

Model	Accuracy	Sensitivity	Specificity	AUC
SVM	0.91	0.82	0.94	0.88
Logistic Regression	0.86	0.83	0.88	0.85
KNN	0.83	0.86	0.82	0.84
AdaBoost (Decision Tree)	0.79	0.9	0.76	0.83
Naive Bayes	0.77	0.9	0.73	0.81
Bagging (Decision Tree)	0.77	0.89	0.72	0.81
Random Forest	0.76	0.92	0.71	0.82
Decision Tree	0.71	0.92	0.65	0.78