ISSN 2348-1196 (print) International Journal of Computer Science and Information Technology Research ISSN 2348-120X (online) Vol. 10, Issue 4, pp: (46-52), Month: October - December 2022, Available at: www.researchpublish.com
Machine Learning Based Model for Prediction of Autism Spectrum Disorder Sandhya A Kulkarni1, Dhanush Vasudevaraju2, C Ramesh Chandra3, Dinesh M4, C Sai Ranganath5 1
Asst.Professor, Department of Computer Science, KSSEM, Bangalore, India
2, 3, 4, 5
Student, Department of Computer Science, KSSEM, Bangalore, India DOI: https://doi.org/10.5281/zenodo.7432991
Published Date: 13-December-2022
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.
I. INTRODUCTION 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 etc, 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 a time efficient, accurate and easy screening test tool is very much required which would predict autism traits in an individual and identify whether or not they require comprehensive autism assessment. The objective of this work is to propose an autism prediction model using ML techniques and to develop a mobile application that could effectively predict autism traits of an individual of any age. In other words, this work focuses on developing an autism screening application for predicting the ASD traits among people of age groups 4-11 years, 12-17 years and for people of age 18 and more.
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