EEG-Based Experiment Design for Major Depressive Disorder - Machine Learning and Psychiatric Diagnosis (Paperback)

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.

General

Imprint:	Academic Press Inc
Country of origin:	United States
Release date:	May 2019
First published:	2019
Authors:	Aamir Saeed Malik • Wajid Mumtaz
Dimensions:	229 x 152 x 20mm (L x W x T)
Format:	Paperback
Pages:	254
ISBN-13:	978-0-12-817420-3
Categories:	Books > Medicine > Other branches of medicine > Psychiatry Promotions
LSN:	0-12-817420-X
Barcode:	9780128174203

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