Identification of Autism Spectrum Disorder (ASD) using Feature-based Machine Learning Classification Model

An evolving brain ailment frequently referred to as Autism Spectrum Disorder (ASD) results in abnormalities in social, language, cognitive, and communication abilities. The two main classifications of interpersonal communication impairment and limited interest/repetitive habits are the focus of the updated ASD diagnostic criteria. Activities can be restricted for people with ASD because of their poor interactions with others and lack of communication. The complex neurodevelopmental disorder known as Autism Spectrum Disorder (ASD) presents enormous challenges in a number of areas, such as behavior, social communication, and sensory processing. ASD is still a complicated and diverse condition with wide-ranging effects on people, families, and society, even with improvements in diagnosis methods and treatment approaches. In addition to addressing important issues and enhancing outcomes for people with ASD, this paper offers a thorough review of current methods in ASD research and clinical practice. Innovative behavioral and pharmacological interventions targeting core symptoms and associated comorbidities, neuroimaging modalities such as diffusion tensor imaging and functional MRI for elucidating underlying neural mechanisms, and machine learning algorithms for early detection and diagnosis are just a few of the techniques that have recently advanced research on ASD. These methods present viable paths. But issues including missed or delayed diagnosis, restricted access to specialized care, social stigma, and inequalities in healthcare and education continue. The proposed goals encompass improving early screening and detection initiatives, endorsing inclusive and accessible therapies and support services, cultivating increased societal understanding and acceptance of ASD, and lobbying for legislation modifications to tackle systemic obstacles. We may work towards a more inclusive and supportive environment for people with ASD and their families by emphasizing these goals and utilizing current technological and scientific developments. This will ultimately improve the quality of life and societal engagement of these people.