Table 5.

Metrics of the best performing ML models in feature selection.

	AUC	Accuracy	Sensitivity	Specificity	Youden index
(a) All patients
Linear SVM	$0.859\pm 0.005$	$0.800\pm 0.005$	$0.416\pm 0.013$	$\mathbf{0.958}\pm \mathbf{0.006}$	$0.374\pm 0.013$
RBF SVM	$\mathbf{0.865}\pm \mathbf{0.007}$	$\mathbf{0.856}\pm \mathbf{0.004}$	$\mathbf{0.621}\pm \mathbf{0.013}$	$0.953\pm 0.003$	$\mathbf{0.575}\pm \mathbf{0.013}$
LASSO	$0.859\pm 0.005$	$0.802\pm 0.004$	$0.452\pm 0.014$	$0.946\pm 0.006$	$0.399\pm 0.012$
Ridge	$0.858\pm 0.005$	$0.796\pm 0.005$	$0.449\pm 0.014$	$0.939\pm 0.007$	$0.388\pm 0.012$
(b) Biopsy GG > 1 patients only
Linear SVM	$\mathbf{0.944}\pm \mathbf{0.004}$	$0.901\pm 0.005$	$0.637\pm 0.023$	$0.936\pm 0.004$	$0.573\pm 0.024$
RBF SVM	$0.894\pm 0.007$	$0.878\pm 0.004$	$0.445\pm 0.024$	$0.936\pm 0.004$	$0.381\pm 0.023$
LASSO	$0.930\pm 0.005$	$0.895\pm 0.005$	$0.613\pm 0.024$	$0.933\pm 0.005$	$0.545\pm 0.023$
Ridge	$\mathbf{0.944}\pm \mathbf{0.005}$	$\mathbf{0.904}\pm \mathbf{0.005}$	$\mathbf{0.652}\pm \mathbf{0.023}$	$\mathbf{0.938}\pm \mathbf{0.004}$	$\mathbf{0.590}\pm \mathbf{0.024}$

The mean scores and their standard deviations of randomly selected 100 train-test splits of (a) all patients and (b) biopsy $\text{GG}>1$ patients only.

Significant values are in bold.