Machine Learning-Based Classification of Autism Spectrum Disorder across Age Groups
K. R. Resmi, Poornima Nanjagoundan Palayam Venkidusamy, G. Raju, Bindu George, Neetha Thomas
Abstract
Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition that has gained significant attention in recent years due to its increasing prevalence and profound impact on individuals, families, and society as a whole. In this study, we explore the use of different machine learning classifiers for the accurate detection of ASD in children, adolescents, and adults. Furthermore, we conduct feature reduction to identify key features contributing to ASD classification within each age group using Cuckoo Search Algorithm. Logistic Regression has the highest accuracy compared to the other two models.
Topics & Concepts
Autism spectrum disorderAutismComputer scienceArtificial intelligenceMachine learningPsychologyDevelopmental psychologyAutism Spectrum Disorder ResearchChild Development and Digital TechnologyGenetics and Neurodevelopmental Disorders