Neural Engineering Techniques for Autism Spectrum Disorder Volume 1 Imaging and Signal Analysis 1st Edition Ayman 0128244224 9780128244227

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Product details:

• ISBN 10: 0128244224
• ISBN 13: 9780128244227
• Author: Ayman S. El-Baz

Neural Engineering for Autism Spectrum Disorder, Volume Two: Diagnosis and Clinical Analysis presents the latest advances in neural engineering and biomedical engineering as applied to the clinical diagnosis and treatment of Autism Spectrum Disorder (ASD). Advances in the role of neuroimaging, magnetic resonance spectroscopy, MRI, fMRI, DTI, video analysis of sensory-motor and social behaviors, and suitable data analytics useful for clinical diagnosis and research applications for Autism Spectrum Disorder are covered, including relevant case studies. The application of brain signal evaluation, EEG analytics, fuzzy model and temporal fractal analysis of rest state BOLD signals and brain signals are also presented.

Table of contents:

Part 1: Autism and clinical analysis: Diagnosis

Chapter 1. Remote telehealth assessments for autism spectrum disorder

Chapter 2. Maternal immune dysregulation and autism spectrum disorder

Chapter 3. Reading differences in eye-tracking data as a marker of high-functioning autism in adults and comparison to results from web-related tasks

Chapter 4. Parents of children with autism spectrum disorders: interventions with and for them

Chapter 5. Applications of machine learning methods to assist the diagnosis of autism spectrum disorder

Chapter 6. Potential approaches and recent advances in biomarker discovery in autism spectrum disorders

Chapter 7. Detection and identification of warning signs of autism spectrum disorder: instruments and strategies for its application

Chapter 8. Machine learning in autism spectrum disorder diagnosis and treatment: techniques and applications

Chapter 9. Inhibition of lysine-specific demethylase 1 enzyme activity by TAK-418 as a novel therapy for autism

Chapter 10. Behavioral phenotype features of autism

Chapter 11. Development of an animated infographic about autistic spectrum disorder

Chapter 12. Fundamentals of machine-learning modeling for behavioral screening and diagnosis of autism spectrum disorder

Chapter 13. A comprehensive study on atlas-based classification of autism spectrum disorder using functional connectivity features from resting-state functional magnetic resonance imaging

Chapter 14. Event-related potentials and gamma oscillations in EEG as functional diagnostic biomarkers and outcomes in auti

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