Table 6.

Comparison of the proposed method with other feature selection methods in the test cohort in terms of classifier performance. The bold values indicate the highest score in each performance metric.

Feature selection method	Accuracy	Minimum sensitivity	Minimum specificity
LASSO	0.8071	0.5273	0.4561
SVM-RFE	0.8014	0.4468	0.3443
mRMR-MIQ	0.7180	0.1600	0.0877
mRMR-MID	0.7055	0.0833	0.0597

LASSO least absolute shrinkage and selection operator, SVM-RFE support vector machine recursive feature elimination, mRMR-MIQ minimum-redundancy maximum-relevancy mutual information quotient, mRMR-MID minimum-redundancy maximum-relevancy mutual information difference.