Role of artificial intelligence in evaluating autism spectrum disorder

Abstract

Autism spectrum disorder (ASD) is a neurological illness characterized by challenges with repetitive tasks, social interaction, and communication. Even if genetics is the primary cause, early detection is vital, and using ML presents a promising way to diagnose the condition more quickly and affordably. In an effort to improve and automate the diagnostic process, this research uses a variety of machine-learning techniques to pinpoint important ASD features. With the rapid growth of artificial intelligence techniques, it has become possible to use intelligent methods to carry out early large-scale senseless screening and diagnosis of autism. In the future, research should focus on building an intelligent medical screening and diagnosis system for autism patients, developing screening tools and constructing an intelligent identification model for patients that integrates multimode data.