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Machine Learning Predicts Phenoconversion from Polysomnography in Isolated REM Sleep Behavior Disord...

Machine Learning Predicts Phenoconversion from Polysomnography in Isolated REM Sleep Behavior Disord...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_994ec47d2ba840f2b8962fc5df4ccbb4

Machine Learning Predicts Phenoconversion from Polysomnography in Isolated REM Sleep Behavior Disorder

About this item

Full title

Machine Learning Predicts Phenoconversion from Polysomnography in Isolated REM Sleep Behavior Disorder

Publisher

Switzerland: MDPI AG

Journal title

Brain sciences, 2024-09, Vol.14 (9), p.871

Language

English

Formats

Publication information

Publisher

Switzerland: MDPI AG

More information

Scope and Contents

Contents

Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is a prodromal stage of alpha-synucleinopathies. This study aimed at developing a fully-automated machine learning framework for the prediction of phenoconversion in patients with iRBD by using data recorded during polysomnography (PSG). A total of 66 patients with iRBD were included,...

Alternative Titles

Full title

Machine Learning Predicts Phenoconversion from Polysomnography in Isolated REM Sleep Behavior Disorder

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_994ec47d2ba840f2b8962fc5df4ccbb4

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_994ec47d2ba840f2b8962fc5df4ccbb4

Other Identifiers

ISSN

2076-3425

E-ISSN

2076-3425

DOI

10.3390/brainsci14090871

How to access this item