The pros and cons of using automated sleep scoring in sleep research.

Sleep automatic sleep classification machine learning

Journal

Sleep
ISSN: 1550-9109
Titre abrégé: Sleep
Pays: United States
ID NLM: 7809084

Informations de publication

Date de publication:
27 Oct 2023
Historique:
received: 03 07 2023
medline: 27 10 2023
pubmed: 27 10 2023
entrez: 27 10 2023
Statut: aheadofprint

Résumé

Sleep scoring plays a pivotal role both in sleep research and in clinical practice. Traditionally, this process has relied on manual scoring by human experts, but it is marred by time constraints, and inconsistencies between different scorers. Consequently, the quest for more efficient and reliable approaches has sparked a great interest in the realm of automatic sleep scoring methods. In this article, we provide an exploration of the merits and drawbacks of automatic sleep scoring, alongside the pressing challenges and critical considerations that demand attention in this evolving field.

Identifiants

pubmed: 37889222
pii: 7331085
doi: 10.1093/sleep/zsad275
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2023. Published by Oxford University Press on behalf of Sleep Research Society.

Auteurs

Abdelrahman Rayan (A)

Donders Institute for Brain, Cognition and Behavior, Radboud University, Postbus 9010, 6500GL Nijmegen Netherlands.

Anna B Szabo (AB)

Research Center on Animal Cognition (CRCA) & Brain and Cognition Research, Toulouse University.

Lisa Genzel (L)

Donders Institute for Brain, Cognition and Behavior, Radboud University, Postbus 9010, 6500GL Nijmegen Netherlands.

Classifications MeSH