Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Apr 22, 2020
Open Peer Review Period: Apr 22, 2020 - Jun 17, 2020
Date Accepted: Sep 4, 2020
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Resting-state EEG used for successful classification of Depression as a novel practice in Psychiatry
ABSTRACT
Machine learning applications in healthcare have become numerous lately, and this work focuses on an important application in psychiatry related to the detection of depression. Since the advent of Computational Psychiatry, valuable research based on fMRI has had phenomenal results, but these tools tend to be simply too expensive for everyday clinical use. Therefore, this article focuses on a much more affordable data-driven approach based on electroencephalographic (EEG) recordings. Further online applications via public or private cloud based platforms would be a logical next step. We have reviewed published studies based on resting state EEG with final machine learning, used to detect depression (detecting studies), while also presenting a group of Interventional studies utilizing some form of stimulation in their method, aimed to predict therapy outcomes. The work concludes with a discussion and review of guidelines to improve the reliability of developed models that may potentially improve diagnostics and offer more accurate treatment of depression in modern psychiatry.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.