Log in to save to my catalogue

Validation of ‘Somnivore’, a Machine Learning Algorithm for Automated Scoring and Analysis of Polyso...

Validation of ‘Somnivore’, a Machine Learning Algorithm for Automated Scoring and Analysis of Polyso...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_491e5d664c6d41a08666b4f5d2c273e7

Validation of ‘Somnivore’, a Machine Learning Algorithm for Automated Scoring and Analysis of Polysomnography Data

About this item

Full title

Validation of ‘Somnivore’, a Machine Learning Algorithm for Automated Scoring and Analysis of Polysomnography Data

Publisher

Switzerland: Frontiers Research Foundation

Journal title

Frontiers in neuroscience, 2019-03, Vol.13, p.207-207

Language

English

Formats

Publication information

Publisher

Switzerland: Frontiers Research Foundation

More information

Scope and Contents

Contents

Manual scoring of polysomnography data is labor-intensive and time-consuming, and most existing software does not account for subjective differences and user variability. Therefore, we evaluated a supervised machine learning algorithm, Somnivore
, for automated wake-sleep stage classification. We designed an algorithm that extracts features from...

Alternative Titles

Full title

Validation of ‘Somnivore’, a Machine Learning Algorithm for Automated Scoring and Analysis of Polysomnography Data

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_491e5d664c6d41a08666b4f5d2c273e7

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_491e5d664c6d41a08666b4f5d2c273e7

Other Identifiers

ISSN

1662-453X,1662-4548

E-ISSN

1662-453X

DOI

10.3389/fnins.2019.00207

How to access this item