TransformEEG, a convolutional-transformer with a depthwise tokenizer, reports the highest median balanced accuracy (78.4-80.1%) and lowest variability across splits among eight EEG models for Parkinson's detection on 290 subjects.
Monte-Silva, Quantitative electroencephalography char- acteristicsforParkinson’sdisease:Asystematicreview,J.Parkinson’s Dis
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TransformEEG: Towards Improving Model Generalizability in Deep Learning-based EEG Parkinson's Disease Detection
TransformEEG, a convolutional-transformer with a depthwise tokenizer, reports the highest median balanced accuracy (78.4-80.1%) and lowest variability across splits among eight EEG models for Parkinson's detection on 290 subjects.