Autism spectrum disorder (ASD) and Alzheimer’s disease (AD) are two significant neurological disorders, which represent the scope of this book. Both ASD and AD affect a significant number of the population and present in numerous ways. This volume covers the state-of-the-art topics that investigate these two significant neurological disorders from a theoretical perspective and focuses on the practical aspects. Materials are presented in a way that can be beneficial to advanced and layman readers and several cutting-edge machine learning techniques for the early diagnosis of ASD are presented in this book. Also, various studies are discussed to demonstrate the formation, cause, and medical treatments for the AD foetal disorder.
Inhaltsverzeichnis
Table of Contents
Preface
Acknowledgement
Dedication
Chapter 1. Machine Learning Applications to Recognize Autism and Alzheimer’s disease
Chapter 2. Neuropathology and Neuroimaging of Alzheimer´s disease
Chapter 3. Retinal Imaging in Alzheimer’s Disease
Chapter 4. Clinically Relevant Depression And Risk Of Alzheimer Disease In Olders: Meta-Analysis Of Cohort Studies
Chapter 5. The Implication of Genetic Factors in Autism Spectrum Disorder and Alzheimer’s disease
Chapter 6. Nuclear Neurology of Autism Spectrum Disorders
Chapter 7. Ethylene and ammonia in neurobehavioral disorders
Chapter 8. Focusing on Parental Behavior Following a Diagnosis of Autism: The Important Role Parents Play and How Stress Can Impact this Role
Chapter 9. Visual saliency for medical imaging and computer-aided diagnosis
Chapter 10. The Early Diagnosis of Alzheimer’s Disease Using Advanced Biomedical Engineering Technology
Chapter 11. A Local/Regional Computer Aided System for the Diagnosis of the Mild Cognitive Impairment
Chapter 12. Identifying Alzheimer’s Disease using Feature Reduction of GLCM and Supervised Classification Techniques
Chapter 13. Current Trends and Considerations of Alzheimer’s Disease
Chapter 14. A Non-Invasive Image-Based Approach Toward an Early Diagnosis of Autism
Chapter 15. Towards a Robust CAD System for Early Diagnosis of Autism Using Structural MRI
Chapter 16. Computational Analysis Techniques: A Case Study on f MRI for Autism Spectrum Disorder
Chapter 17. Autism Diagnosis Using Task-Based Functional MRI
Über den Autor
Ayman El-Baz is a professor, university scholar and the chair of the Bioengineering Department at the University of Louisville, Kentucky. He earned his BSc and MSc in electrical engineering in 1997 and 2001, respectively. He earned his Ph D in electrical engineering from the University of Louisville in 2006, and has 17 years of hands-on experience in the fields of bio-imaging modeling and non-invasive computer-assisted diagnosis systems.Jasjit S Suri is an innovator, scientist, visionary, industrialist and internationally known world leader in biomedical engineering. He has spent more than 25 years in the field of biomedical engineering and its management, and in 2018 he was awarded the Marquis Life Time Achievement Award for his outstanding contributions and dedication to medical imaging and its management.
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