Diagnosis Of Autism Spectrum Disorder Based On Functional Brain Networks And Machine Learning

This paper presents a method for the automatic diagnosis of autism based on functional brain imaging data recorded from 500 subjects. The method is based on Bootstrap Analysis of Stable Cluster map and can distinguish the control group from autism spectrum disorder patients with high accuracy. The functional brain networks of autism spectrum disorder patients show more segregation, less distribution of information across the network, and less connectivity compared to the control cases.