P137 Deep learning enables accurate automatic sleep stage classification in a clinical paediatric population

INTRODUCTION: Sleep disorders are widespread in children and associated with a myriad of detrimental health sequelae. Accurate identification of sleep stages is crucial in diagnosing various sleep disorders; however, manual sleep stage scoring can be subjective, laborious, and costly. To tackle thes...

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Detalles Bibliográficos
Autores principales: Somaskandhan, P, Korkalainen, H, Terrill, P, Sigurðardóttir, S, Arnardóttir, E, Ólafsdóttir, K, Clausen, M, Töyräs, J, Leppänen, T
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Poster Presentations
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10109032/
http://dx.doi.org/10.1093/sleepadvances/zpab014.178

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10109032/
http://dx.doi.org/10.1093/sleepadvances/zpab014.178

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