Table 2:

Highest predictive performances of different models in identifying the molecular features of glioblastomas in IDH wild-type lower-grade gliomas in the test set

Model	Feature Selection + Classifier	AUC	P Values for Model Comparisons
Model 1 (clinical features)	NA	0.514 (0.356–0.672)
Model 2 (VASARI features)	NA	0.648 (0.511–0.784)
Model 3 (VASARI + radiomics features)	RFE + SVM	0.854 (0.766–0.941)	<.001^{^a}	.023^{^b}
Model 4 (clinical + VASARI + radiomics features)	RFE + SVM	0.863 (0.778–0.947)	<.001^{^a}	.02^{^b}	.476^{^c}

Note:—NA indicates not applicable.
↵a Compared with model 1.
↵b Compared with model 2.
↵c Compared with model 3.