Predictive approach for Autism Detection using Computer Vision and Deep Learning

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition that profoundly impacts social interactions, behavior, and communication in individuals. Accurate and timely detection of ASD is crucial for effective intervention and management of the disorder. In recent years, the field of artificial intelligence (AI) has significantly contributed to the diagnosis and screening of ASD, aiding clinicians and researchers alike. This article offers a comprehensive review of the current state of using AI for ASD detection. Various AI methodologies, including machine learning algorithms, natural language processing techniques, and deep learning models, are discussed in the context of ASD diagnosis. The paper highlights how AI can automate ASD assessment, enhance diagnostic accuracy, and identify early signs of the disorder. Additionally, the paper explores the challenges and limitations associated with AI-based approaches for ASD detection. Overall, this article serves as a valuable resource for clinicians, developers, and researchers interested in leveraging AI technologies to advance ASD detection and improve outcomes for individuals on the autism spectrum.