An interpretable model based on graph learning for diagnosis of Parkinson’s disease with voice-related EEG
Parkinson’s disease (PD) exhibits significant clinical heterogeneity, presenting challenges in the identification of reliable electroencephalogram (EEG) biomarkers. Machine learning techniques have been integrated with resting-state EEG for PD diagnosis, but their practicality is constrained…
Continue Reading