1. A computer-implemented method for assessing a traumatic brain injury (TBI) in a patient, the method comprising: obtaining diffusion magnetic resonance imaging (dMRI) data from the patient; obtaining resting-state functional magnetic resonance imaging (rs-fMRI) data from the patient; extracting connectivity features between different regions of a brain of the patient, the connectivity features extracted from the rs-fMRI data obtained from the patient and/or from the diffusion magnetic resonance imaging (dMRI) data obtained from the patient; extracting network features from the connectivity features; and determining a TBI diagnosis for the patient based on at least the network features and the connectivity features using a trained classifier.
1. A computer-implemented method for assessing a traumatic brain injury (TBI) in a patient, the method comprising: obtaining diffusion magnetic resonance imaging (dMRI) data from the patient; obtaining resting-state functional magnetic resonance imaging (rs-fMRI) data from the patient; extracting connectivity features between different regions of a brain of the patient, the connectivity features extracted from the rs-fMRI data obtained from the patient and/or from the diffusion magnetic resonance imaging (dMRI) data obtained from the patient; extracting network features from the connectivity features; and determining a TBI diagnosis for the patient based on at least the network features and the connectivity features using a trained classifier. 11. The computer-implemented method of claim 1 , further comprising: outputting a prediction confidence associated with the TBI diagnosis for the patient.