<ul data-eligibleForWebStory="false"><li>Electroencephalography (EEG) is being used for early detection of Parkinson's Disease.</li><li>Deep Learning models for EEG-based PD detection lack generalizability due to high inter-subject variability.</li><li>A new model called TransformEEG is introduced, combining Convolutional-Transformer architecture.</li><li>TransformEEG shows improved performance in PD detection with reduced variability and increased consistency.</li></ul>

TransformEEG: Towards Improving Model Generalizability in Deep Learning-based EEG Parkinson's Disease Detection

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