Artificial Intelligence and Machine Learning in Autism Detection: From Common to Rare Disorders

Autism is an attitude-driven issue that generally resulted in negative stigma toward anyone. Autism is related to a developmental disability that is caused because of differences in the brain. People with autism problem generally have social communication and interaction problems. It is not always that people having autism issue experience developmental disability; however, this issue can also originate from other diseases as well. Autism disorder is categorized into common and rare diseases. Under common autism disorder, autism spectrum and attention deficit hyperactivity disorder. Research has been conducted to detect and correct the issues associated with common autism disorders. AI and machine-learning-based mechanisms are available for the detection of common autism-related diseases. For rare, autism-related diseases, limited work has been done. For rare autism including Rett syndrome and childhood disintegrative disorder can be screened with tests. Rare AD screening tests however are time- and money-consuming. Techniques including machine learning are researched over with the help of which detection of ASD and ADHD and decide whether to get a clinical test for the same or not based on generated predictions. AD is not curable disease however technology-driven methodology can be used for early detection and avoiding additional harm to the body. In modern era, artificial intelligence and machine-learning-based mechanism have been evolved to complement the traditional clinical tests for the diagnosis of AD. The focus of this paper is to explore the AI and machine-learning-based mechanisms along with clinical tests that are used for detection of AD. Furthermore, this paper finds out the most significant mechanism used for the classification of AD-based disease. Rare disease however yet not explored with technology and hence open issues and challenges associated with rare diseases has been explored through this research.