ASD-SAENet: A Sparse Autoencoder, and Deep-Neural Network Model for Detecting Autism Spectrum Disorder (ASD) Using fMRI Data

Autism spectrum disorder (ASD) is a heterogenous neurodevelopmental disorder which is characterized by impaired communication, and limited social interactions. The shortcomings of current clinical approaches which are based exclusively on behavioral observation of symptomology, and poor understandin...

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Veröffentlicht in:	Frontiers in computational neuroscience Jg. 15; S. 654315
Hauptverfasser:	Almuqhim, Fahad, Saeed, Fahad
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland Frontiers Research Foundation 08.04.2021 Frontiers Media S.A
Schlagworte:	ABIDE ASD Autism autoencoder Biomarkers Brain mapping Classification Data acquisition Datasets Deep learning fMRI Functional magnetic resonance imaging Medical imaging Neural networks Neurodevelopmental disorders Neuroimaging Neuroscience Social interactions sparse autoencoder fMRI ASD autoencoder deep-learning sparse autoencoder diagnosis ABIDE classification
ISSN:	1662-5188, 1662-5188
Online-Zugang:	Volltext
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