Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method

Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method

The whole-brain functional connectivity (FC) pattern obtained from resting-state functional magnetic resonance imaging data are commonly applied to study neuropsychiatric conditions such as autism spectrum disorder (ASD) by using different machine learning models. Recent studies indicate that both h...

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Bibliographic Details
Main Authors: Xinyu Guo, Kelli C. Dominick, Ali A. Minai, Hailong Li, Craig A. Erickson, Long J. Lu
Format: Article
Language:English
Published: Frontiers Media S.A. 2017-08-01
Series:Frontiers in Neuroscience
Subjects:
autism spectrum disorder
resting-state fMRI
deep neural network
sparse auto-encoder
feature selection
Online Access:http://journal.frontiersin.org/article/10.3389/fnins.2017.00460/full

Internet

http://journal.frontiersin.org/article/10.3389/fnins.2017.00460/full

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