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EEG-Based Experiment Design for Major Depressive Disorder : Machine Learning and Psychiatric Diagnosis

By: (Author) Aamir Saeed Malik , (Author) Wajid Mumtaz

Manufactured on Demand
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Ksh 20,700.00

Format: Paperback / Softback

ISBN-10: 012817420X

ISBN-13: 9780128174203

Publisher: Elsevier Science Publishing Co Inc

Imprint: Academic Press Inc

Country of Manufacture: NL

Country of Publication: GB

Publication Date: May 17th, 2019

Print length: 254 Pages

Weight: 424 grams

Dimensions (height x width x thickness): 15.20 x 22.80 x 2.00 cms

Product Classification: Psychiatry

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EEG-Based Experiment Design for Major Depressive Disorder: Machine Learning and Psychiatric Diagnosis introduces EEG-based machine learning solutions for diagnosis and assessment of treatment efficacy for a variety of conditions. With a unique combination of background and practical perspectives for the use of automated EEG methods for mental illness, it details for readers how to design a successful experiment, providing experiment designs for both clinical and behavioral applications. This book details the EEG-based functional connectivity correlates for several conditions, including depression, anxiety, and epilepsy, along with pathophysiology of depression, underlying neural circuits and detailed options for diagnosis. It is a necessary read for those interested in developing EEG methods for addressing challenges for mental illness and researchers exploring automated methods for diagnosis and objective treatment assessment.

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