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Neural Engineering Techniques for Autism Spectrum Disorder, Volume 2
Diagnosis and Clinical Analysis
Examines the latest applications of Neural Networks applied to diagnosis of key types of cancer
Jasjit Suri (Edited by), Ayman S. El-Baz (Edited by)
9780128244210
Paperback, published 25 October 2022
346 pages
23.5 x 19 x 2.2 cm, 0.7 kg
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.
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
Subject Areas: Biomedical engineering [MQW]
