Functional connectivity-based classification of autism and control using SVM-RFECV on rs-fMRI data

•The proposed method improves the identification of autism on resting-state functional magnetic imaging data.•The most discriminative feature subset about functional connectivity in the brain of autism was found.•The classification accuracy obtained is better than the recent similar studies.•The res...

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Bibliographic Details
Published in:	Physica medica Vol. 65; pp. 99 - 105
Main Authors:	Wang, Canhua, Xiao, Zhiyong, Wu, Jianhua
Format:	Journal Article
Language:	English
Published:	Italy Elsevier Ltd 01.09.2019
Subjects:	Adolescent Adult Autism Autistic Disorder - diagnostic imaging Case-Control Studies Child Classification Feature selection Female fMRI Humans Image Processing, Computer-Assisted - methods Machine learning Magnetic Resonance Imaging Male Support Vector Machine Young Adult Autism fMRI Feature selection Machine learning Classification
ISSN:	1120-1797, 1724-191X, 1724-191X
Online Access:	Get full text
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