Autism Detection Analysis Through Behavioral and Genetic Analysis using Random Forest and XGBoost Algorithm

The Autism Detection and Treatment Management System leverages machine learning algorithms for early autism spectrum disorder (ASD) detection and personalized treatment planning. This PHP MySQL full-stack website integrates user-friendly interfaces for data input and analysis. The system employs supervised learning models trained on extensive behavioral and diagnostic datasets to accurately identify potential ASD indicators in individuals. Features include comprehensive profiling, aiding clinicians in tailored intervention strategies. Real- time monitoring and feedback mechanisms enable ongoing assessment and adjustment of treatment plans. The system facilitates collaborative efforts among healthcare providers, educators, and caregivers, fostering a holistic approach to ASD management. Its secure, scalable architecture ensures data confidentiality and accessibility. Through innovative technology and data-driven insights, this system strives to enhance early detection and optimize personalized care for individuals on the autism spectrum.