Title: A systematic study of intelligent autism spectrum disorder detector

Authors: Indu Jamwal; Deepti Malhotra; Mehak Mengi

Addresses: Department of Computer Science and IT, Central University of Jammu, Jammu and Kashmir, India ' Department of Computer Science and IT, Central University of Jammu, Jammu and Kashmir, India ' Department of Computer Science and IT, Central University of Jammu, Jammu and Kashmir, India

Abstract: Autism spectrum disorder also known as ASD is a complex developmental condition particularly related to the nervous system that affects people's communication, social behaviour, and underlying social knowledge. The problem of autism is not common to a particular age group but it has been ascending rapidly among all age groups. Earlier prediction of this developmental disorder will grandly help in sustentation of the subject's physical as well as mental soundness. With more advancement in technology, early detection of certain neurological disorders now becomes reality. Mostly machine-learning methods are used for the analysis of ASD. This research paper presents the systematic review of existing AI models for ASD detection based on screening methods, eye movements, and MRI data, and based on limitations of existing studies, the authors have proposed an ASD_esfMRI for earlier detection of autism which can be implemented in future by using eye gaze data and MRI data collectively.

Keywords: autism spectrum disorder; ASD; machine learning; magnetic resonance imaging; MRI; structural MRI; functional MRI; neurological; detection; prediction.

DOI: 10.1504/IJCVR.2023.129435

International Journal of Computational Vision and Robotics, 2023 Vol.13 No.2, pp.219 - 234

Received: 13 Jan 2021
Accepted: 01 Feb 2022
Published online: 09 Mar 2023 *

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