Simple 1-D Convolutional Networks for Resting-State fMRI Based Classification in Autism

Published: Jul 1, 2019
Abstract
Deep learning methods are increasingly being used with neuroimaging data like structural and function magnetic resonance imaging (MRI) to predict the diagnosis of neuropsychiatric and neurological disorders. For psychiatric disorders in particular, it is believed that one of the most promising modality is the resting-state functional MRI (rsfMRI), which captures the intrinsic connectivity between regions in the brain. Because rsfMRI data points...
Paper Details
Title
Simple 1-D Convolutional Networks for Resting-State fMRI Based Classification in Autism
Published Date
Jul 1, 2019
Journal
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