Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Automatic Diagnosis of Autism Spectrum Disorder Detection Using a Hybrid Feature Selection Model with Graph Convolution Network Subject The topic of the resource ABFO; Autism spectrum disorder; Graph convolutional networks; mRMR; SVM-RFE Description An account of the resource A neurodevelopmental disorder is called an autism spectrum disorder (ASD) that influences a persons assertion, interaction, and learning abilities. The consequences and severity of symptoms of ASD will vary from person to person; the disorder is mainly diagnosed in children aged 15years and older, and its symptoms may include unusual behaviors, interests, and social challenges. If it is not resolved at this stage, it will become severe in the coming days. So, in this manuscript, we propose a way to automatically tell if someone has ASD that works well by using a combination of feature selection and deep learning. Four phases comprise the proposed model: preprocessing, feature extraction, feature selection, and prediction. At first, the collected images are given to the preprocessing stage to remove the noise. Then, for each image, three types of features are extracted: the shape feature, texture feature, and histogram feature. Then, optimal features are selected to minimize computational complexity and time consumption using a new technique based on a combination of adaptive bacterial foraging optimization (ABFO), support vector machines-recursive feature elimination (SVM-RFE), minimum redundancy and maximum relevance (mRMR). Then, the graph convolutional network (GCN) classifier uses the selected features to identify an image as normal or autistic. According to the research observations, our models accuracy is enhanced to 97.512%. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Lamani M.R.; Benadit P.J. Source A related resource from which the described resource is derived SN Computer Science, Vol-5, No. 1 Publisher An entity responsible for making the resource available Springer Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s42979-023-02439-z" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s42979-023-02439-z</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180210216&amp;doi=10.1007%2Fs42979-023-02439-z&amp;partnerID=40&amp;md5=b01c9cae8e1de2938bc2945e56cff620" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180210216&amp;doi=10.1007%2fs42979-023-02439-z&amp;partnerID=40&amp;md5=b01c9cae8e1de2938bc2945e56cff620</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 2662995X Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Lamani M.R., CHRIST (Deemed to be University), Computer Science and Engineering, Karnataka, Bangalore, 560074, India; Benadit P.J., CHRIST (Deemed to be University), Computer Science and Engineering, Karnataka, Bangalore, 560074, India