Figure 3.

(A) Nested cross-validation classification accuracy of random forest models for classifying patients as short-term (ST) versus Long-term (LT) survivors based on median survival. The overall accuracy of the model was 83.3%. The model correctly classified ST with 89.7% accuracy and LT with 76% accuracy. (B) The top 10 strongest features used by the random forest for survival classification based on embedded feature selection. The strongest features included age and various brain regions at different scales.