Comprehensive Analysis of Autism Spectrum Disorder Detection Using Deep Learning

Autism Spectrum Disorder (ASD) is a complex neurological condition characterized by a wide range of symptoms. Early and accurate diagnosis is crucial for effective intervention and support. This research reviews the established diagnostic tools, including clinical assessments, behavioral observations, genetic testing, and neuroimaging techniques. Additionally, we explore the potential of emerging technologies like machine learning and AI-based approaches in enhancing ASD diagnosis. By analyzing the strengths and limitations of various detection methods, this research provides a comprehensive overview of the current state of the field. The findings highlight the importance of continued research and innovation in improving ASD diagnosis for the benefit of affected individuals and their families.