AUTISM SPECTRUM DISORDER DETECTION USING MACHINE LEARNING

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dc.contributor.authorBolatkhan, Adilet
dc.date.accessioned2024-06-20T08:29:56Z
dc.date.available2024-06-20T08:29:56Z
dc.date.issued2024-04-23
dc.description.abstractThis article examines the visual preferences of autistic children in order to identify specific patterns, such as repetitive behavior, and focus on certain elements of the visual content, such as geometric shapes, etc. To analyze visual preferences, the research team collected the experimental data of two groups of children: those diagnosed with Autism Spectrum Disorders and typically developing children. Based on the received data, a model was trained to detect autism with the usage of machine learning. In addition, the machine was safely tested on children and showed the possibility of detecting Autism Spectrum Disorders in 40% of children with autism. The study was conducted on a web platform specially designed for the young audience, which allows them to track the direction of their gaze. The obtained results also indicate that children with autism give visual preference to geometric shapes with dynamic scene changes. The implementation of this system will be useful for early detection of Autism Spectrum Disorders due to the wide accessibility of this web platform and its beneficence as a reliable screening tool. The aim of the research is to create an innovative software that will provide an opportunity to identify Autism Spectrum Disorder using machine learning.en_US
dc.identifier.citationBolatkhan, A. (2024). "Autism Spectrum Disorder Detection Using Machine Learning," Nazarbayev University Graduate School of Engineering and Digital Sciencesen_US
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/7909
dc.language.isoenen_US
dc.publisherNazarbayev University Graduate School of Engineering and Digital Sciencesen_US
dc.subjectAutism Spectrum Disorderen_US
dc.subjectMachine Learningen_US
dc.subjectLong-term Short-term Memoryen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectweb-platformen_US
dc.subjectwebgazeren_US
dc.subjectvisual preferencesen_US
dc.subjecteye-trackingen_US
dc.subjectType of access: Restricteden_US
dc.titleAUTISM SPECTRUM DISORDER DETECTION USING MACHINE LEARNINGen_US
dc.typeMaster's thesisen_US
workflow.import.sourcescience

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