Survey on Prediction of Autism Spectrum Disorder

Machine learning is a sort of synthesized intelligence that enables software programs to predict outcomes more correctly. It is believed that old information employed as inputs in a mechanical research algorithm will yield new values. It is important since it provides businesses with information about customer and retailer behaviour patterns that can be used to improve new products. Autism spectrum disorders are more prevalent than ever today. Screening tests are costly and time-consuming when used to discover autistic symptoms. The advancement of artificial intelligence & ML enables the early detection of autism. We collected datasets on ASD that were discovered early and connected to newborn, children, and adults. We then applied various natural conversion algorithms to these datasets. Various typing approaches were performed on these adjusted ASD datasets, and their performance was evaluated. This system employs categorization algorithms such as Random Forest, SVM, AdaBoost, and ANN. A neurological condition called autism spectrum disorder or ASD impairs a person's capacity for communication, expression, and comprehension. Even though it can be diagnosed at any age, most symptoms start showing up in the early years and worsen over time. Autism patients have a wide range of challenges, including sensory impairments, mobility difficulties, learning disabilities, mental health disorders such as anxiety and depression, and many others.