Abstract
Major depressive disorder (MDD) affects women more severely than men1, particularly in Iran where prevalence is two-fold.2 There is no current research available for such sex differences in repetitive transcranial magnetic stimulation (rTMS), an efficacious MDD treatment.3 Electroencephalography (EEG) serves as biomarker for rTMS treatment given its high temporal resolution, non-invasiveness, and relative affordability. 4,5 Deep learning (DL) algorithms can further classify these EEG signals to predict treatment responses.6 In this study, five different EEG-based deep learning (DL) models were created to classify male and female subjects using their pre- and post-TMS raw EEG data.
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