A systematic study of intelligent autism spectrum disorder detector

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.