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Diagnosis of Autism Spectrum Disorder: A Review of Three Focused Interventions

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Abstract

Autism is a neurological developmental disorder that impacts a person’s physical, social, and emotional behavior. This disorder develops over time and is characterized by social deficits and repetitive behavior. Although there is no cure for this disorder, an early diagnosis and intervention can do significant wonders and can help the subject to become active functioning members of the family and society. The aim of this study is to minimize the diagnostic period by finding an optimal diagnosis procedure from the existing diagnosis tools. The diagnosis of autism can be done in three ways: 1. clinical evaluation; 2. screening tools; 3. brain images. In this review paper, we have thoroughly gone through all three types of diagnostic procedures and found that there was no single diagnostic tool to confirm the disorder. We also found that the diagnosis period was too long. As the result of this review, we found an ASD diagnosis triad which helps to choose the right diagnosis procedure based on the subjects age which reduces the diagnostic period and helps to aid early diagnosis by eliminating the chaos in choosing the diagnostic tools.

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  1. Christ University, Bangalore, India

    D. Swainson Sujana

  2. Department of Computer Science, Christ University, Bangalore, India

    D. Peter Augustine

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This article is part of the topical collection “Advances in Computational Intelligence, Paradigms and Applications” guest edited by Young Lee and S. Meenakshi Sundaram.

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Sujana, D.S., Augustine, D.P. Diagnosis of Autism Spectrum Disorder: A Review of Three Focused Interventions. SN COMPUT. SCI. 4, 139 (2023). https://doi.org/10.1007/s42979-022-01584-1

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