Log in to save to my catalogue

EEG-based machine learning models for the prediction of phenoconversion time and subtype in isolated...

EEG-based machine learning models for the prediction of phenoconversion time and subtype in isolated...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2925002235

EEG-based machine learning models for the prediction of phenoconversion time and subtype in isolated rapid eye movement sleep behavior disorder

About this item

Full title

EEG-based machine learning models for the prediction of phenoconversion time and subtype in isolated rapid eye movement sleep behavior disorder

Publisher

US: Oxford University Press

Journal title

Sleep (New York, N.Y.), 2024-05, Vol.47 (5), p.1

Language

English

Formats

Publication information

Publisher

US: Oxford University Press

More information

Scope and Contents

Contents

Abstract
Study Objectives
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 electro...

Alternative Titles

Full title

EEG-based machine learning models for the prediction of phenoconversion time and subtype in isolated rapid eye movement sleep behavior disorder

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_miscellaneous_2925002235

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2925002235

Other Identifiers

ISSN

0161-8105

E-ISSN

1550-9109

DOI

10.1093/sleep/zsae031

How to access this item