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 Multi-atlas Graph Convolutional Networks and Convolutional Recurrent Neural Networks-Based Ensemble Learning for Classification of Autism Spectrum Disorders Subject The topic of the resource Autism spectrum disorder; Automatic diagnosis; Deep learning; Ensemble learning; Graph convolution network Description An account of the resource Autism spectrum disorder (ASD) has an influence on social conversation and interaction, as well as encouraging people to engage in repetitive behaviors. The complication begins in childhood and persists through adolescence and maturity. Autism spectrum disorder has become the most common kind of childhood development worldwide. ASD hinders the capacity to interact, socialize, and build connections with individuals of all ages, and thus its early intervention is critical. This paper discusses some of the most recent approaches to diagnostics using convolutional networks and multi-atlas graphs for autism spectrum disorders. Also, several pre-processing approaches are elaborated. Graph convolutional neural networks (GCNs) to diagnose autism spectrum disorder (ASD) because of their remarkable effectiveness in illness prediction using multi-site data. Convolutional neural network (CNN) and recurrent neural networks (RNN) infrastructure studies functional connection patterns between various brain regions to find particular patterns to diagnose ASD. In our research, we implemented the GCN + CRNN ensemble method and achieved 89.01% accuracy based on resting-state data from the fMRI (ABIDE-II), a novel framework for detecting early signs of autism spectrum disorders is presented and discussed. 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.; Vaithinathan K. Source A related resource from which the described resource is derived SN Computer Science, Vol-4, No. 3 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 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s42979-022-01617-9" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s42979-022-01617-9</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148413670&amp;doi=10.1007%2Fs42979-022-01617-9&amp;partnerID=40&amp;md5=96c448a9976c631411ea1c2339c34478" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148413670&amp;doi=10.1007%2fs42979-022-01617-9&amp;partnerID=40&amp;md5=96c448a9976c631411ea1c2339c34478</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., Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Benadit P.J., Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Vaithinathan K., Computer Engineering, Karaikal Polytechnic College, Varichikudy, Karaikal, India