An established subset of neurological disorders is known as autism spectrum disorder (ASD). Communication and social interaction ability may suffer a lifetime effect as a result of ASD. Autism symptoms begin appearing in children as early as three years old, and they continue to intensify as they get older, into adolescence and adulthood. ASD recovery is made possible by earlier diagnosis and prediction. In many medical and healthcare systems, machine learning algorithms are used widely. In this study, a variety of machine learning classification and regression models are applied to the electronic health records of pregnant women who had children with ASD in order to identify the disease at an early stage. The aim of this research is to make early ASD predictions.

Autism, classification, Regression, Electronic Health Records, Gestational Period.