Beyond Augmentation: Score-Guided Pathological Prior for EEG-based Depression Detection

arXiv:2606.00180v1 Announce Type: new Abstract: Deep learning-based Major Depressive Disorder (MDD) detection using Electroencephalography (EEG) is fundamentally constrained by the "small-sample dilemma." Prevailing generative data augmentation methods not only incur heavy computational overhead but also risk introducing synthetic noise, thereby blurring classification boundaries. To challenge the traditional "data quantity first" convention, we propose a novel framework "Beyond Augmentation": Score-Guided Classification (SGC). SGC does not synthesize pseudo-samples; instead, it utilizes an un

Source: arXiv cs.LG — read the full report at the original publisher.

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