1. A method for automated diagnosis of attention deficit hyperactivity disorder (ADHD), comprising: extracting anatomical features from a structural magnetic resonance image (MRI) of a patient; extracting functional features from a resting-state functional MRI (rsFMRI) series of the patient, comprising: extracting an rsFMRI time series for each of a plurality of brain regions by mapping voxels in each of a plurality of image volumes in the rsFMRI series to a plurality of brain regions and extracting an rsFMRI time series for each brain region based on the voxels mapped to that brain region in the plurality of image volumes in the rsFMRI series by calculating, for each of M brain regions, an average of voxels mapped to that brain region in each of N image volumes in the rsFMRI series, resulting in an M ×N matrix including the rsFMRI time series for each of the brain regions, and extracting the functional features based on the rsFMRI time series for each of the plurality of brain regions; and determining an ADHD diagnosis for the patient based on the anatomical features, the functional features, and phenotypic features of the patient using a trained machine learning classifier.