A Review on using Artificial Neural Network in Diagnosis of Autism Spectrum Disorder

Lakhwinder Kaur*, Vikas Khullar**
* Postgraduate, Department of Computer Science and Engineering, CT Institute of Engineering, Management and Technology, Shahpur.
** Assistant Professor, Department of Computer Science and Engineering, CT Institute of Engineering, Management and Technology, Shahpur.
Periodicity:March - May'2017
DOI : https://doi.org/10.26634/jcom.5.1.13795

Abstract

This paper discusses the concept of autism, its signs and symptoms, diagnosis and various technologies being used for diagnosis and treatment of autistic children. Autism is qualitative impairments in social interaction, communication and repetitive patterns of behavior. Autistic children can be treated as non communicative, non interactive and non responsive. The term autism was firstly used by Bleuler in 1908 to describe any patient and firstly described by Leo kanner in 1943. Autistic children suffer from mild, moderate, and severe levels of autistic behaviour. Mild level autistic children have few abnormal actitivites. Moderate level autistic children have moderate abnormal activities. Severe level autistic children have high abnormal functional activities. Autistic children symptoms can be easily seen within age of 18 to 30 months. Various methods of artificial intelligence are used for the diagnosis of activities or levels of autistic children by using various CHATS like CARS, ADI, ADOS, and DSMs. Various artificial neural network and fuzzy based system are used for detecting the severity levels of autism. By using the artificial neural networks and fuzzy system we can diagnose a child whether he is autistic or not.

Keywords

Autism, Artificial Neural Network, Fuzzy Expert System, DSMs

How to Cite this Article?

Kaur, L., and Khullar, V. (2017). A Review on using Artificial Neural Network in Diagnosis of Autism Spectrum Disorder. i-manager’s Journal on Computer Science, 5(1), 38-45. https://doi.org/10.26634/jcom.5.1.13795

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