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
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.