Marina Yusoff Universiti Teknologi MARA
Autism Spectrum Disorder (ASD) remains an enigmatic and complex neurodevelopmental disorder, particularly in children. Despite ongoing research, understanding the causes and effects of ASD is still evolving. Current diagnostic approaches are often expensive, time-consuming, and heavily reliant on the expertise of medical professionals, who may not always be readily available due to training or interest gaps. This project proposes an innovative Autism Spectrum disorder prediction System called AutiSense, utilizing artificial intelligence (AI) methods to address these challenges. AutiSense is a system that will be able to predict autism in toddlers. The goal is to provide a system that is user-friendly and as accurate as possible for the early prediction of autism in toddlers. AutiSense employed advanced machine learning to analyze behavioral patterns. By identifying subtle signs, the system can detect autism in toddlers at an early stage, allowing for timely intervention and support. Expert validation of the system yielded a 100% validation score, demonstrating its potential effectiveness in early ASD detection in children. People who might have autism traits are successfully put into a category. AutiSense benefits to the public, health agencies, NGOs, and health professionals and has great potential for commercialization.
