附註:Includes bibliographical references and index.
Chapter 1. Application of image processing for autism spectrum disorder -- Chapter 2. A novel neuro-fuzzy system-based autism spectrum disorder -- Chapter 3. A novel technique on autism spectrum disorders using classification techniques -- Chapter 4. A novel automated approach for deep learning on stereotypical autistic motor movements -- Chapter 5. Machine learning techniques for analysing and identifying autism spectrum disorder -- Chapter 6. ML-PASD: predict autismspectrum disorder by machine learning approach -- Chapter 7. Existing assistive techniques for dyslexics: a systematic review -- Chapter 8. Mouse-less cursor control for quadriplegic and autistic patients using artificial intelligence -- Chapter 9. Optimization of machine learning models for early diagnosis of autism spectrum disorder.
摘要:Autism spectrum disorder (ASD) is known as a neuro-disorder in which a person may face problems in interaction and communication with people, amongst other challenges. As per medical experts, ASD can be diagnosed at any stage or agebut is often noticeable within the first two years of life. If caught early enough, therapies and services can be provided at this early stage instead of waiting until it is too late. ASD occurrences appear to have increased over the last couple of years leading to the need for more research in the field. It is crucial to provide researchers and clinicians with the most up-to-date information on the clinical features, etiopathogenesis, and therapeutic strategies for patientsas well as to shed light on the other psychiatric conditions often associated with ASD. In addition, it is equally important to understand how to detect ASD in individuals for accurate diagnosing and early detection.
