  We consider a problem of diagnostic pattern recognition/classification from
neuroimaging data. We propose a common data analysis pipeline for
neuroimaging-based diagnostic classification problems using various ML
algorithms and processing toolboxes for brain imaging. We illustrate the
pipeline application by discovering new biomarkers for diagnostics of epilepsy
and depression based on clinical and MRI/fMRI data for patients and healthy
volunteers.
