Tools

LEADER 04132cam a2200589 i 4500

001 on1102049110;

003 OCoLC;

005 20221026165823.0;

006 m o d ;

007 cr cnu|||unuuu;

008 190522s2019 enka ob 001 0 eng d;

015 a| GBB9975442| bnb;

019 a| 1235834808;

020 a| 9780128174210q| (electronic bk.);

020 a| 0128174218q| (electronic bk.);

035 a| (Sirsi) o1102049110;

035 a| (OCoLC)1102049110z| (OCoLC)1235834808;

049 a| NEHH;

050 4 a| RC386.6.E43;

060 4 a| WM 171.5;

082 04 a| 616.80475472| 23;

100 1 a| Malik, Aamir Saeed,d| 1969-e| author.=| ^A1443100;

245 10 a| EEG-based experiment design for major depressive disorder :b| machine learning and psychiatric diagnosis /c| Aamir Saeed Malik, Wajid Mumtaz.;

264 1 a| London :b| Academic Press,c| 2019.;

300 a| 1 online resource (xvii, 235 pages) :b| illustrations (some color);

336 a| textb| txt2| rdacontent;

337 a| computerb| c2| rdamedia;

338 a| online resourceb| cr2| rdacarrier;

504 a| Includes bibliographical references and index.;

588 0 a| Online resource; title from PDF title page (EBSCO, viewed May 23, 2019).;

520 a| 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.;

505 0 a| 1. Introduction: Depression and Challenges; 2. EEG Fundamentals; 3. EEG-Based Brain Functional Connectivity and Clinical Implications; 4. Pathophysiology of Depression; 5. Using EEG for Diagnosing and Treating Depression; 6. Neural Circuits and EEG Based Neurobiology for Depression; 7. Design of EEG Experiment for Assessing MDD; 8. EEG-based Diagnosis of Depression; 9. EEG-based Treatment Efficacy Assessment Involving Depression;

650 0 a| Electroencephalographyx| Methodology.=| ^A1408;

650 0 a| Depression, Mental.=| ^A352;

650 0 a| Brainx| Research.=| ^A182657;

650 12 a| Major Depressive Disorderx| diagnosis0| (DNLM)D003865Q000175=| ^A1336221;

650 12 a| Electroencephalographyx| methods0| (DNLM)D004569Q000379=| ^A925574;

650 22 a| Machine Learning0| (DNLM)D000069550=| ^A1345552;

650 2 a| Brain.=| ^A917911;

650 2 a| Depression.=| ^A917718;

655 0 a| Electronic books.=| ^A491897;

700 1 a| Mumtaz, Wajid,e| author.=| ^A1443471;

856 40 z| Direct link to ebook u| https://ebookcentral.proquest.com/lib/eastcarolina/detail.action?docID=5777785;

949 a| CLICK ON WEB ADDRESSw| ASISh| HSL102p| $176.400| HSLo| HJH;

949 a| CLICK ON WEB ADDRESS w| ASIS h| JOYNER96 o| HJH;

994 a| C0b| NEH;

596 a| 1 4;

998 a| 5879387;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 5879387-1001l| HSLELECm| HSLp| $176.40r| Ys| Yt| HGENEBKu| 7/28/2022x| EBOOKz| HERESOURCE0| HSLo| .STAFF. HJH;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 5879387-2001l| JNETm| JOYNERr| Ys| Yt| JNE3BKu| 7/28/2022x| EBOOKz| JERESOURCEo| .STAFF. HJH;

EEG-based experiment design for major depressive disorder : machine learning and psychiatric diagnosis / Aamir Saeed Malik, Wajid Mumtaz.

Author/creator	Malik, Aamir Saeed, 1969- author.
Other author	Mumtaz, Wajid, author.
Format	Electronic
Publication	London : Academic Press, 2019.
Description	1 online resource (xvii, 235 pages) : illustrations (some color)
Supplemental Content	Direct link to ebook
Subjects	Electroencephalography--Methodology. Depression, Mental. Brain--Research. Major Depressive Disorder--diagnosis. Electroencephalography--methods. Machine Learning Brain. Depression.

Contents	1. Introduction: Depression and Challenges; 2. EEG Fundamentals; 3. EEG-Based Brain Functional Connectivity and Clinical Implications; 4. Pathophysiology of Depression; 5. Using EEG for Diagnosing and Treating Depression; 6. Neural Circuits and EEG Based Neurobiology for Depression; 7. Design of EEG Experiment for Assessing MDD; 8. EEG-based Diagnosis of Depression; 9. EEG-based Treatment Efficacy Assessment Involving Depression
Abstract	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.
Bibliography note	Includes bibliographical references and index.
Source of description	Online resource; title from PDF title page (EBSCO, viewed May 23, 2019).
Issued in other form	Print version: Malik, Aamir Saeed. EEG-based experiment design for major depressive disorder : machine learning and psychiatric diagnosis. London, United Kingdom : Academic Press, an imprint of Elsevier, 2019 255 pages 9780128174203
Genre/form	Electronic books.
ISBN	9780128174210 (electronic bk.)
ISBN	0128174218 (electronic bk.)

Availability

Library	Location	Call Number	Status	Item Actions
	Electronic Resources	Access Content Online	✔ Available

EEG-based experiment design for major depressive disorder : machine learning and psychiatric diagnosis / Aamir Saeed Malik, Wajid Mumtaz.

Click here for more information about this title

Availability