Autism Spectrum Disorder Diagnosis using Optimal Machine Learning Methods

Maitha Rashid Alteneiji,Layla Mohammed,Muhammad Usman

doi:10.14569/ijacsa.2020.0110929

Maitha Rashid Alteneiji, Layla Mohammed + Show 1 more

Open Access

https://doi.org/10.14569/ijacsa.2020.0110929

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Abstract

Autism spectrum disorder (ASD) is the disorder of communication and behavior that affects children and adults. It can be diagnosed at any stage of life. Most importantly, the first two years of life, regardless of ethnicity, race, or economic groups. There are different variations of ASD according to the severity and type of symptoms experienced by people. It is a lifelong disorder, but treatment and services can improve the symptoms. The literature focuses on one of the main methods used by physicians to diagnose ASD. Many types of research and medical reports have been reviewed; however, a few of them only give good medical results for the strong differentiation of ASD from healthy people. This paper focuses on using machine learning algorithms to predict an individual with specific ASD symptoms. The target is to predict an individual with specific ASD symptoms and finding the best machine learning model for diagnosis. Further, the paper aims to make the autism diagnosis faster to deliver the required treatment at an early stage of child development.

Highlights

IntroductionThe main aim of the paper is to use artificial intelligence and machine-learning models that can help in medical fields by finding the optimal model that can recognize individuals with specific Autistic Spectrum Disorder symptoms [8]
Artificial Intelligence has increasing importance in society
The data used in this paper mainly focuses on diagnosing individuals with Autism spectrum disorder (ASD) symptoms, based on Autism Spectrum Quotient (AQ)-10 with several variables that usually affect the diagnosing result

Summary

Introduction

The main aim of the paper is to use artificial intelligence and machine-learning models that can help in medical fields by finding the optimal model that can recognize individuals with specific Autistic Spectrum Disorder symptoms [8]. Since early intervention affords the best opportunity to support healthy development and deliver benefits across the lifespan, this paper helps parents to recognize if their child has an ASD at an early age [4,7]. It has a value in the health sector since there is no valid health reason for this disease. This work shows the power of machine learning algorithms in detecting individuals with specific Autistic Spectrum Disorder symptoms [5]

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