Predicting treatment response using EEG in major depressive disorder: A machine-learning meta-analysis.

ABSTRACT: Selecting a course of treatment in psychiatry remains a trial-and-error process, and this long-standing clinical challenge has prompted an increased focus on predictive models of treatment response using machine learning techniques. Electroencephalography (EEG) represents a cost-effective and scalable potential measure to predict treatment response to major depressive disorder. We performed separate meta-analyses to determine the ability of models to distinguish between responders and non-responders using EEG across treatments, as well as a performed subgroup analysis of response to transcranial magnetic stimulation (rTMS), and antidepressants (Registration Number: CRD42021257477) in Major Depressive Disorder by searching PubMed, Scopus, and Web of Science for articles published between Ja

SUBMITTER: Watts D 

PROVIDER: S-EPMC9374666 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature