Detecting Autism Spectrum Disorder (ASD) Using Machine Learning

This paper focuses on using eye tracking technology to detect autism spectrum disorder (ASD) in children.Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by challenges in social communication and repetitive behaviors.Early diagnosis and intervention are crucial for optimizing developmental outcomes in children with ASD.This study explores the feasibility of utilizing eye tracking technology and machine learningalgorithms to detect potential indicators of ASD in children The number of peoplewith autism has increased in recent years.The disorder is characterized by cognitive inexperience that affects the nervous system and children’s growth and development.It appears frequently in the first few years of a child’s life and has a negative effect on visual behavior.Machine learning (ML) has a lot of potential to classify this problem.In this paper, a program for diagnosing autism was built by eye in the Python language and machine-learning technology to support vector machines with the use of a computer vision algorithm known as ViolaJones.The algorithm has achieved an accuracy of 89%.