Abstract
This chapter aims to classify context-specific subjects as either treatment responders or nonresponders to antidepressant medication. The method used includes the Intelligent Treatment Management System (ITMS). The ITMS performs electroencephalography (EEG)-based prediction of treatment outcomes of antidepressant therapy (ITMS-treatment selection), while classifying major depressive disorder (MDD) patients as either treatment respondents (R) or nonrespondents (NR) based on pretreatment EEG data acquired from MDD patients. The EEG-based scheme presented in this chapter inherently involves subprocesses such as noise removal from EEG data, EEG-based feature extraction, feature selection, classification, and validation, including 10-fold cross-validation (10-CV). This chapter provides technical details regarding these subprocesses.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: EEG-Based Experiment Design for Major Depressive Disorder
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
