8. The computer-implemented method of claim 1 , wherein the determining of the TBI diagnosis for the patient using the trained classifier comprises: determining the TBI diagnosis using a plurality of trained classifiers based on a subset of features selected from at least the network features and the connectivity features of the patient.
8. The computer-implemented method of claim 1 , wherein the determining of the TBI diagnosis for the patient using the trained classifier comprises: determining the TBI diagnosis using a plurality of trained classifiers based on a subset of features selected from at least the network features and the connectivity features of the patient. 9. The computer-implemented method of claim 8 , wherein the determining of the TBI diagnosis using the plurality of trained classifiers comprises: calculating a respective TBI diagnosis prediction from each of the plurality of trained classifiers; calculating a weighted average of the respective TBI diagnosis predictions, wherein each respective TBI prediction is weighted based on a performance level of the corresponding trained classifier in predicting TBI diagnoses of training examples; and determining the TBI diagnosis for the patient based on the weighted average of the respective TBI diagnosis predictions.