Fig. 2.

The ROC curves for the glioma-grading predictive model in the training and validation set. A: In the training set, the AUC is 82.5%. At the optimal cutoff value (0.4), the sensitivity, specificity, and accuracy are 74.2%, 81.4%, and 78.38%, respectively (red dot). B: In the validation set, the AUC of the predictive model is 82.0%. At the best cutoff point (0.8), the sensitivity, specificity, and accuracy were 89.5%, 63.2%, and 76.31%, respectively (red dot).