Employing Machine Learning-Based Predictive Analytical Approaches to Classify Autism Spectrum Disorder Types

Autism spectrum disorder is an inherited long-living and neurological disorder that starts in the early age of childhood with complicated causes. Autism spectrum disorder can lead to mental disorders such as anxiety, miscommunication, and limited repetitive interest. If the autism spectrum disorder...

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Main Authors: Muhammad Kashif Hanif, Naba Ashraf, Muhammad Umer Sarwar, Deleli Mesay Adinew, Reehan Yaqoob
Format: Article
Language:English
Published: Hindawi-Wiley 2022-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2022/8134018
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author Muhammad Kashif Hanif
Naba Ashraf
Muhammad Umer Sarwar
Deleli Mesay Adinew
Reehan Yaqoob
author_facet Muhammad Kashif Hanif
Naba Ashraf
Muhammad Umer Sarwar
Deleli Mesay Adinew
Reehan Yaqoob
author_sort Muhammad Kashif Hanif
collection DOAJ
description Autism spectrum disorder is an inherited long-living and neurological disorder that starts in the early age of childhood with complicated causes. Autism spectrum disorder can lead to mental disorders such as anxiety, miscommunication, and limited repetitive interest. If the autism spectrum disorder is detected in the early childhood, it will be very beneficial for children to enhance their mental health level. In this study, different machine and deep learning algorithms were applied to classify the severity of autism spectrum disorder. Moreover, different optimization techniques were employed to enhance the performance. The deep neural network performed better when compared with other approaches.
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spelling doaj.art-9a214b90cfe24937a30cd7e12063d7c32024-11-02T05:32:30ZengHindawi-WileyComplexity1099-05262022-01-01202210.1155/2022/8134018Employing Machine Learning-Based Predictive Analytical Approaches to Classify Autism Spectrum Disorder TypesMuhammad Kashif Hanif0Naba Ashraf1Muhammad Umer Sarwar2Deleli Mesay Adinew3Reehan Yaqoob4Department of Computer ScienceDepartment of Computer ScienceDepartment of Computer ScienceDepartment of Computer ScienceDepartment of Computer ScienceAutism spectrum disorder is an inherited long-living and neurological disorder that starts in the early age of childhood with complicated causes. Autism spectrum disorder can lead to mental disorders such as anxiety, miscommunication, and limited repetitive interest. If the autism spectrum disorder is detected in the early childhood, it will be very beneficial for children to enhance their mental health level. In this study, different machine and deep learning algorithms were applied to classify the severity of autism spectrum disorder. Moreover, different optimization techniques were employed to enhance the performance. The deep neural network performed better when compared with other approaches.http://dx.doi.org/10.1155/2022/8134018
spellingShingle Muhammad Kashif Hanif
Naba Ashraf
Muhammad Umer Sarwar
Deleli Mesay Adinew
Reehan Yaqoob
Employing Machine Learning-Based Predictive Analytical Approaches to Classify Autism Spectrum Disorder Types
Complexity
title Employing Machine Learning-Based Predictive Analytical Approaches to Classify Autism Spectrum Disorder Types
title_full Employing Machine Learning-Based Predictive Analytical Approaches to Classify Autism Spectrum Disorder Types
title_fullStr Employing Machine Learning-Based Predictive Analytical Approaches to Classify Autism Spectrum Disorder Types
title_full_unstemmed Employing Machine Learning-Based Predictive Analytical Approaches to Classify Autism Spectrum Disorder Types
title_short Employing Machine Learning-Based Predictive Analytical Approaches to Classify Autism Spectrum Disorder Types
title_sort employing machine learning based predictive analytical approaches to classify autism spectrum disorder types
url http://dx.doi.org/10.1155/2022/8134018
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