“School of Biological”
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| Paper IPM / Biological / 14674 |
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| Abstract: | |||||||||||||
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Studies on autism spectrum disorder (ASD) have indicated several dysfunctions in the structure, and
functional organization of the brain. However, findings have not been established as a general diagnostic tool
yet. In this regard, current study proposed an automatic screening method for recognition of ASDs from
healthy controls (HCs) based on their brain functional abnormalities. In this paradigm, brain functional
networks of 60 adolescent and young adult males (29 ASDs and 31 HCs) were estimated from subjects�?? task-
free fMRI data. Then, autism screening was developed based on characteristics of the functional networks
using the following steps: A) local and global parameters of the brain functional network were calculated
using graph theory. B) network parameters of the ASDs were statistically compared to the HCs. C)
significantly altered parameters were used as input features of the screening system. D) performance of the
system was verified using various classification techniques. The support vector machine showed superiority
to others with an accuracy of 92dataset including 20 ASDs and 20 HCs. Our findings suggest that local parameters of the brain functional
network, despite the individual variability, can potentially be used for autism screening.
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