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Dementia with Lewy body disease (DLB) is the second leading cause of degenerative cognitive disorder after Alzheimer's disease (AD). Its variable clinical expression makes diagnosis difficult. To date, there is no validated DLB diagnostic biomarker, despite several biomarkers in development (EEG, MRI, biology). Studies have shown that an improvement in diagnostic performance could be obtained by combining different modalities biomarkers using machine learning. The aim of this research is to identify the best combination of multimodal biomarkers for the diagnosis of DLB (EEG, MRI, biology, cognitive scores), using a machine learning approach applied to a clinical cohort.
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