EEG-based Machine Learning Models for the Prediction of Phenoconversion Time and Subtype in iRBD

Exploring foci of: bioRxiv (Cold Spring Harbor Laboratory) EEG-based Machine Learning Models for the Prediction of Phenoconversion Time and Subtype in iRBD September 2023 • El Jeong, Yong Woo Shin, Jung‐Ick Byun, Jun‐Sang Sunwoo, Monica Roascio, Pietro Mattioli, Laura Giorgetti, Francesco Famà, Gabriele Arnulfo, Dario Ar… Abstract Background Idiopathic/Isolated rapid eye movement sleep behavior disorder (iRBD) is a prodromal stage of α-synucleinopathies and eventually phenoconverts to overt neurodegenerative diseases including Parkinson’s disease (PD), dementia with Lewy bodies (DLB) and multiple system atrophy (MSA). Associations of baseline resting-state electroencephalography (EEG) with phenoconversion have been reported. Objectives In this study, we aimed to develop machine learning models to predict phenoconversion time and su… Open Article Page

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