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The significance of clinical EEG abnormalities in …
https://pubmed.ncbi.nlm.nih.gov/7850395/
An Improved Classification Model for Depression …
https://pubmed.ncbi.nlm.nih.gov/32340958/
Electroencephalogram (EEG) and eye movements (EMs) data have been widely used for depression detection due to their advantages of easy recording and non-invasion. This research proposes a content based ensemble method (CBEM) to promote the depression detection accuracy, both static and dynamic CBEM were discussed.
Using EEG to Predict Clinical Response to …
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8264052/
Introduction. Electroconvulsive therapy (ECT) is among the oldest and most effective therapy for the treatment of depressive disorders, more effective than pharmacotherapy ().ECT has demonstrated response rates between 60 and 80% and remission rates between 50 and 60% ().Indications in depressive disorders are life-threatening psychotic, suicidal features …
EEG-based deep learning model for the automatic …
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