Autism spectrum disorder (ASD) is one of the most significant neurological disorders that disrupt a person's social communication skills. The progression and development of neuroimaging technologies has made structural network construction of brain regions possible. In this paper, after finding the discriminative sub-network using the evolutionary algorithm, the simple features of the sub-network lead us to diagnose autism in various subjects with plausible accuracy (76% on average). This method yields substantially better results compared to previous researches. Thus, this method may be used as an accurate assistance in autism screening
@article{arxiv.1911.05484,
title = {Extracting a Discriminative Structural Sub-Network for ASD Screening using the Evolutionary Algorithm},
author = {M. Amin and F. Safaei and N. S. Ghaderian},
journal= {arXiv preprint arXiv:1911.05484},
year = {2019}
}