Computational Intelligence in Detection and Support of Autism Spectrum Disorder

Sabbir Ahmed, Silvia Binte Nur, Md. Farhad Hossain, M. Shamim Kaiser, Mufti Mahmud, Tianhua Chen

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Autism Spectrum Disorder (ASD) refers to a spectrum of conditions characterised mainly by impairments in social interaction, speech and nonverbal communication, and restricted—repetitive behaviour. The lack of physical testing, done primarily via behaviour analysis, makes ASD diagnosis more difficult. The emergence of Computational Intelligence techniques has resulted in the development of a variety of fast and early ASD diagnosis methods based on multiple input modalities. The premise of computational intelligence (CI) and its efficiency in detecting and monitoring ASD has been examined in this chapter, which has recently advanced. Two types of studies have been discussed in this article. Several aspects of ASD screening, including questionnaires, eye scan paths, movement tracking, behavioural analysis from video, brain scans, and more, have been discussed using machine learning and deep learning. Secondly, ASD detection and monitoring applications have been studied extensively in the past year, with significant advances. Finally, a discussion has been made on the challenges faced in ASD detection and management with future research scopes.
Original languageEnglish
Title of host publicationArtificial Intelligence in Healthcare
Subtitle of host publicationRecent Applications and Developments
EditorsTianhua Chen, Jenny Carter, Mufti Mahmud, Arjab Singh Khuman
PublisherSpringer Singapore
Number of pages19
ISBN (Electronic)9789811952722
ISBN (Print)9789811952715
Publication statusPublished - 26 Oct 2022

Publication series

NameBrain Informatics and Health
PublisherSpringer Singapore
ISSN (Print)2367-1742
ISSN (Electronic)2367-1750


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