Screening For Childhood Autism Spectrum Disorder Using Machine Learning

Screening For Childhood Autism Spectrum Disorder Using Machine Learning

T. Vedhakshari1, A. Bhargav Kumar2, R. Sneha Latha Reddy3, J. Narendra Shiva Sai4, V.L. Sowjanya5

[1-4] B.Tech Student, [5] Assistant Professor, LIET

[1,2,3,4,5] Computer Science and Systems Engineering, Lendi Institute of Engineering and Technology, Vizianagaram.

Abstract – Autism Spectrum Disorder (ASD) affects communication, behavior, and social interactions, and early detection is crucial for intervention. Current diagnostic method sare subjective and prone to delays or misdiagnosis. This project explores machine learning (ML) to automate ASD screening using behavioral data, diagnostic questionnaires, and developmental milestones. Supervised learning algorithms classify children into ASD or non-ASD categories with high accuracy. The approach aims to assist clinicians in early identification and intervention. It offers a scalable, efficient, and objective screening tool for ASD in clinical and educational settings.

Key Words: Autism Spectrum Disorder (ASD), Machine Learning, Early Detection, Screening, Behavioral Data, Supervised Learning, Diagnostic Tools, Developmental Milestones, Classification, Intervention, Artificial Intelligence, Predictive Modeling, Child Development, Healthcare Technology, Autism Diagnosis.