A Review of Autism Spectrum Disorder Detection Using Machine Learning Techniques

Autism is one of the mental diseases that many societies are dealing with today. This disease is classified into different levels. The problem of autism spectrum disorder (ASD) have been mounting swiftly nowadays among all ages of the human population. Early detection of this neurological disease can greatly assist in the maintenance of the subject’s mental and physical health. The symptoms of this problem may be started at the age of three years and may continue for the lifetime. It is not possible to complete treat the patient suffering from this disease, however its effects can be reduced for some time if the symptoms are early detected. In order to prevent the progression of symptoms, it is necessary to determine which category the patient is in. In this article, we have investigated different methods of diagnosis and classification of this disease in patients of different ages using machine learning methods. In this article, we have reviewed four articles and their methods. These articles include: Use of machine learning to shorten observation-based screening and diagnosis of autism, Analysis and Detection of Autism Spectrum Disorder Using Machine Learning Techniques, Searching for a minimal set of behaviors for autism detection through feature selection-based machine learning, Applying Machine Learning to Identify Autism With Restricted Kinematic Features

Keywords:

Autism detection , machine learning , autism disorder