Author Description

The book explores the prevalence of ASD and the challenges associated with its early detection. Recognizing the limitations of existing diagnostic methods, the volume emphasizes the need for a multidisciplinary approach, utilizing the collective strengths of artificial intelligence (AI), biomedical engineering, and applied neuroscience. This convergence promises not only to enhance diagnostic accuracy but also to streamline the process, facilitating timely interventions for improved treatment. Key Features: Illustrates the latest advancements in AI, biomedical engineering, and applied neuroscience, providing readers with a comprehensive overview of cutting-edge technologies in autism detection. Integrates diverse perspectives from leading experts, merging the fields of AI, biomedical engineering, and neuroscience to present a unified and multidisciplinary approach to autism diagnosis. Demonstrates the practical applications of innovative diagnostic tools, from machine learning algorithms to biomedical devices, offering real-world insights and case studies for effective implementation. Explores the future directions of autism detection, discussing emerging technologies and ethical considerations. Guides readers through a journey of discovery, unraveling the complexities of autism spectrum disorders, and empowering healthcare professionals, researchers, and students with actionable knowledge for enhanced diagnosis and support.