Abstract: Autism spectrum disorder is a neurodevelopmental disorder that affects a person's interaction, communication and learning skills. Although diagnosis of autism can be done at any age, its symptoms generally appear in the first two years of life and develop through time. Autism patients face different types of challenges such as difficulties with concentration, learning disabilities, mental health problems such as anxiety, depression, motor difficulties, sensory problems, and many others. Diagnosis of autism requires significant amount of time and cost. Earlier detection of autism can come to a great help by prescribing patients with proper medication at an early stage. It can prevent the patient's condition from deteriorating further and would help to reduce long term costs associated with delayed diagnosis. Thus, an efficient, accurate and easy screening test tool is very much required which would predict autism traits in an individual. The main idea behind this project is to detect autism spectrum disorder in an individual (male/female). This project is implemented by making use of a Machine Learning model using parameters such as an individual's age, gender, ethnicity, Autism Quotient Tool. The detection derived from this project will help an individual to get required diagnosis in time to prevent further complications of developing Alzheimer's disease.
Keywords: machine learning, autism spectrum disorder, parameters, autism quotient tool.
Title: Machine Learning Based Model for Prediction of Autism Spectrum Disorder
Author: Sandhya A Kulkarni, Dhanush Vasudevaraju, C Ramesh Chandra, Dinesh M, C Sai Ranganath
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
Vol. 10, Issue 4, October 2022 - December 2022
Page No: 46-52
Research Publish Journals
Website: www.researchpublish.com
Published Date: 13-December-2022
