Early detection of autism spectrum disease in children

Abstract

Autism Spectrum Disorders (“ASD”) is a neurodevelopmental disorder whose symptoms appear in the first years of a child's life. These symptoms are characterized as a lack of communication skills (verbal and nonverbal) used in social interaction and a way of responding to sensory and environmental stimuli that manifest as restricted and repetitive behavioral patterns. In this research, the focus will be on diagnosing the disease through a set of tests in which a foreground-backward neural network is trained and taught.And through the results obtained, the disease is diagnosed for the affected person. The tests are based on diagnostic information about the parents as well as information about the child. From the results obtained, it was found that the success rate of the diagnosis is up to 90%.VB Net (Visual basic.Net) was used to configure the neural network