ASD Diagnosis in Children, Adults, and Adolescents using Various Machine Learning Techniques

ASD, often known as an autism spectrum disorder, is a neurodevelopmental condition that impairs a person’s capacity for successful social interaction and communication. The long-term results for individuals affected can be significantly improved by early detection and proper diagnosis of this disorder. Traditional diagnostic techniques, however, might take a while and are not always accurate. In order to solve these challenges, this study investigates the use of machine learning to diagnose ASD. The research uses a big dataset of behavioral and demographic data from individuals with and without autism to train and evaluate machine learning algorithms. The findings imply that these algorithms can identify autism with more accuracy than current techniques. This implies that machine learning may be a useful technique for making an early and precise diagnosis of ASD