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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Vydané v:	Journal of neuroscience methods Ročník 343; s. 108840
Hlavní autori:	Wang, Yufei, Wang, Jianxin, Wu, Fang-Xiang, Hayrat, Rahmatjan, Liu, Jin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Netherlands Elsevier B.V 01.09.2020
Predmet:	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
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