Functional Magnetic Resonance Imaging (fMRI) is a medical imaging technique used to capture brain activity under various conditions. Using fMRI scans, deviations in brain activity can be identified and related to specific mental disorders such as ADHD, anxiety, and depression. Currently, the trajectory of identifying a mental disorder within the patient and finding the right treatment relies on extensive periods of trial-and-error with various medications resulting in long treatment and unwanted side-effects. Radiomics, which consists of quantitative MRI analysis and subsequent data-mining with deep learning, may aid the process of identifying the right treatment early on for patients. This project focuses on using fMRI data to either identify mental disorders and explain the disease using related biomarkers in the brain, or leverage longitudinal data to identify alterations in brain activity which indicate successful treatment.