Table 7.

Comparison of the proposed method with other classifiers in the test cohort. The bold values indicate the highest score in each performance metric.

Classifier	Accuracy	Minimum sensitivity	Minimum specificity
XGBoost	0.8071	0.5273	0.4561
Random forest	0.8037	0.5179	0.4035
SVM	0.7911	0.4730	0.4035
k-NN	0.7717	0.4355	0.3333

SVM support vector machine, k-NN k-nearest neighbor.