Deep Multimodal Learning for the Diagnosis of Autism Spectrum Disorder

dc.contributor.authorTang, Michelle
dc.contributor.authorKumar, Pulkit
dc.contributor.authorChen, Hao
dc.contributor.authorShrivastava, Abhinav
dc.date.accessioned2023-11-09T17:39:16Z
dc.date.available2023-11-09T17:39:16Z
dc.date.issued2020-06-10
dc.description.abstractRecent medical imaging technologies, specifically functional magnetic resonance imaging (fMRI), have advanced the diagnosis of neurological and neurodevelopmental disorders by allowing scientists and physicians to observe the activity within and between different regions of the brain. Deep learning methods have frequently been implemented to analyze images produced by such technologies and perform disease classification tasks; however, current state-of-the-art approaches do not take advantage of all the information offered by fMRI scans. In this paper, we propose a deep multimodal model that learns a joint representation from two types of connectomic data offered by fMRI scans. Incorporating two functional imaging modalities in an automated end-to-end autism diagnosis system will offer a more comprehensive picture of the neural activity, and thus allow for more accurate diagnoses. Our multimodal training strategy achieves a classification accuracy of 74% and a recall of 95%, as well as an F1 score of 0.805, and its overall performance is superior to using only one type of functional data.
dc.description.urihttps://doi.org/10.3390/jimaging6060047
dc.identifierhttps://doi.org/10.13016/dspace/cdek-m7vs
dc.identifier.citationTang, M.; Kumar, P.; Chen, H.; Shrivastava, A. Deep Multimodal Learning for the Diagnosis of Autism Spectrum Disorder. J. Imaging 2020, 6, 47.
dc.identifier.urihttp://hdl.handle.net/1903/31333
dc.language.isoen_US
dc.publisherMDPI
dc.relation.isAvailableAtCollege of Computer, Mathematical & Natural Sciencesen_us
dc.relation.isAvailableAtComputer Scienceen_us
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_us
dc.relation.isAvailableAtUniversity of Maryland (College Park, MD)en_us
dc.subjectdeep learning
dc.subjectnultimodal learning
dc.subjectconvolutional neural networks
dc.subjectautism
dc.subjectfMRI
dc.titleDeep Multimodal Learning for the Diagnosis of Autism Spectrum Disorder
dc.typeArticle
local.equitableAccessSubmissionNo

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