Machine Learning and Neurological Disorders

This chapter explores the integration of machine learning with neuroimaging techniques to understand and treat neurological and psychiatric disorders. It focuses on utilizing resting state fMRI data for predicting clinical severity, particularly in autism spectrum disorder, and emphasizes the challenges and advancements in data analysis. The discussion highlights the importance of structured approaches, such as dictionary learning and connectivity matrices, in improving predictive models and enhancing clinical interventions.