A convolutional recurrent neural network with attention for response prediction to repetitive transcranial magnetic stimulation in major depressive disorder
Abstract:Prediction of response to Repetitive Transcranial Magnetic Stimulation (rTMS) can build a very effective treatment platform that helps Major Depressive Disorder (MDD) patients to receive timely treatment. We proposed a deep learning model powered up by state-of-the-art methods to classify responders (R) and non-responders (NR) to rTMS treatment. Pre-treatment Electro-Encephalogram (EEG) signal of public TDBRAIN dataset and 46 proprietary MDD subjects were utilized to create time–frequency representations using… Show more
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