Neural Engineering Techniques for Autism Spectrum Disorder, Volume 2

Diagnosis and Clinical Analysis
Herausgeber: S. El-Baz, Ayman; Suri, Jasjit

• Broschiertes Buch

Produktbeschreibung

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. A clinical guide for general practitioners is provided along with a variety of assessment techniques such as magnetic resonance spectroscopy. The book is presented in two volumes, including Volume One: Imaging and Signal Analysis Techniques comprised of two Parts: Autism and Medical Imaging, and Autism and Signal Analysis. Volume Two: Diagnosis and Treatment includes Autism and Clinical Analysis: Diagnosis, and Autism and Clinical Analysis: Treatment.

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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Verlag: Elsevier Science Publishing Co Inc
• Seitenzahl: 346
• Erscheinungstermin: 25. Oktober 2022
• Englisch
• Abmessung: 193mm x 235mm x 21mm
• Gewicht: 716g
• ISBN-13: 9780128244210
• ISBN-10: 0128244216
• Artikelnr.: 63467542

Inhaltsangabe

1. Remote Telehealth Assessments for Autism Spectrum Disorder 2. Maternal
Immune Dysregulation and Autism Spectrum Disorder 3. Reading differences in
eye-tracking data as a marker of high-functioning autism in adults and
comparison to results from web-related tasks 4. Parents of Children with
Autism Spectrum Disorders: Intervention with and for Them 5. Applications
of Machine Learning to Assist the Diagnosis of Autism Spectrum Disorder 6.
Potential Approaches and recent advances in biomarker discovery in autism
spectrum disorder 7. Detection and Identification of warning signs of
autism spectrum disorder: instruments and strategies for its application 8.
Machine Learning in Autism Spectrum Disorder Diagnosis and treatment:
techniques and applications 9. Inhibition of LSD1 Enzyme activity by
TAK-418 as a novel therapy for autism 10. Behavioral Phenotype features of
Autism Spectrum Disorder 11. Development of an animated infographic about
autism spectrum disorder 12. Fundamentals of Machine Learning modelling in
Behavioral screening and diagnosis of autism spectrum disorder 13. A
comprehensive study on Atlas-based classification of autism spectrum
disorder using functional connectivity features from resting state fMRI 14.
Event-related potentials and gamma oscillations in EEG as functional
diagnostic biomarkers and outcomes in autism spectrum disorder treatment
research