Fuzzy Based Approaches for Autism Spectrum Disorder Detection: A Review

Autism Spectrum Disorder is a neurodevelopment state manifest through difficulties with community interaction, constrained repetitive activity patterns and, the presence of specific interests or occupations. ASD is mainly caused by genetics or by environmental factors; however, its condition can be improved by treating and detecting ASD at its earlier stages. There are many ways to detect ASD, including psychological exams and neuro imaging modalities. Fuzzy logic is working in many sophisticated applications of artificial intelligence, including natural language processing. Fuzzy logic simulates human decision-making, but much more quickly. The main and the foremost objective of this paper is to represent an overview and provide the in-detail briefing of fuzzy logic methodology and concepts for detection of ASD. This paper discusses a systematic and literature review through a variety of scholarly and academic research papers, professional expert discussions and online databases. The goal of this study is to examine Fuzzy logic based expert systems for ASD identification.