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A Deep Neural Network-Based Model for Screening Autism Spectrum Disorder Using the Quantitative Checklist for Autism in Toddlers (QCHAT).

Autism spectrum disorder (ASD) is an abnormal condition of brain development characterized by impaired cognitive ability, speech and human interactions, in addition to a set of repetitive and stereotyped patterns of behaviours. Although no cure for autism exists, early medical intervention can impro...

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Published in:Journal of Autism & Developmental Disorders Vol. 52; no. 6; pp. 2732 - 2747
Main Authors: Mujeeb Rahman, K. K., Monica Subashini, M.
Format: equations & formulas research tables/charts Journal Article
Published: Springer Nature Jun2022
Online Access:View this record in EBSCOhost
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      dt: Jun2022
      vid: 52
      iid: 6
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10803-021-05141-2
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        atl: A Deep Neural Network-Based Model for Screening Autism Spectrum Disorder Using the Quantitative Checklist for Autism in Toddlers (QCHAT).
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        au:
          Mujeeb Rahman, K. K.
          Monica Subashini, M.
        affil: Department of Biomedical Engineering, Ajman University, Ajman, United Arab Emirates
      sug:
        subj:
          Autism Spectrum Disorder Diagnosis
          Neural Networks (Computer)
          Health Screening
          Checklists
          Human
          Algorithms
          Minimum Data Set
          Early Intervention
          Quality of Life
          Problem Solving
          Child
          Child: 6-12 years
      ab: Autism spectrum disorder (ASD) is an abnormal condition of brain development characterized by impaired cognitive ability, speech and human interactions, in addition to a set of repetitive and stereotyped patterns of behaviours. Although no cure for autism exists, early medical intervention can improve the associated symptoms and quality of life. Several manually executed screening tools help to identify the ASD-related behavioural traits in the children that assists the specialist in diagnosing the disease accurately. The quantitative checklist for autism in toddlers (QCHAT) is one of the efficient screening tools used worldwide for ASD screening. ASD diagnosis requires many different manually administered procedures; hence long delay is encountered in getting final results. In recent years, deep neural network (DNN) popularity has been immensely increasing due to its supremacy in solving complex problems. The objective of this research is to apply algorithms, based on the deep neural network (DNN) to identify patients with ASD from the QCHAT datasets. We have used two datasets, the QCHAT and QCHAT-10, in our study. The results obtained show that related to contemporary techniques, the proposed method brings better performance.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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