Detection and Prediction of Autism Spectrum Disorder Using AI Techniques: A Review

Abstract

Typical designations for autism include a developmental disability that lasts a lifetime. The traits associated with autism spectrum disorder (ASD) are repetitive behavior, nonverbal communication, and difficulty focusing. ASD needs to be diagnosed early because it has been growing more quickly in recent years. It costs a lot of money and time to figure out autism utilizing several testing methods. Predictive analytics, another name for various AI models, has gained prominence recently. In medical science, machine learning, deep learning, and pattern recognition are the main examples of multidisciplinary research areas that offer efficient methods for diagnosing ASD. This paper aims to analyze various algorithms for deep learning (DL) and machine learning (ML) and compare the outcomes focusing on precision and effectiveness.