AIMAFE: Autism spectrum disorder identification with multi-atlas deep feature representation and ensemble learning

•Multi-atlas functional connectivity is calculated as the original feature representation.•Multi-atlas deep feature representation is extracted by a deep learning method.•An ensemble learning strategy is proposed to perform the final ASD identification task.•Our proposed method achieves classificati...

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Bibliographic Details

Published in:	Journal of neuroscience methods Vol. 343; p. 108840
Main Authors:	Wang, Yufei, Wang, Jianxin, Wu, Fang-Xiang, Hayrat, Rahmatjan, Liu, Jin
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier B.V 01.09.2020
Subjects:	Autism spectrum disorder identification Ensemble learning Functional connectivity Functional magnetic resonance imaging Stacked denoising autoencoder Functional connectivity Functional magnetic resonance imaging Ensemble learning Stacked denoising autoencoder Autism spectrum disorder identification
ISSN:	0165-0270, 1872-678X, 1872-678X
Online Access:	Get full text
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