Cargando…
Deep learning-based algorithm accurately classifies sleep stages in preadolescent children with sleep-disordered breathing symptoms and age-matched controls
INTRODUCTION: Visual sleep scoring has several shortcomings, including inter-scorer inconsistency, which may adversely affect diagnostic decision-making. Although automatic sleep staging in adults has been extensively studied, it is uncertain whether such sophisticated algorithms generalize well to...
Autores principales: | Somaskandhan, Pranavan, Leppänen, Timo, Terrill, Philip I., Sigurdardottir, Sigridur, Arnardottir, Erna Sif, Ólafsdóttir, Kristín A., Serwatko, Marta, Sigurðardóttir, Sigurveig Þ., Clausen, Michael, Töyräs, Juha, Korkalainen, Henri |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10140398/ https://www.ncbi.nlm.nih.gov/pubmed/37122306 http://dx.doi.org/10.3389/fneur.2023.1162998 |
Ejemplares similares
-
P137 Deep learning enables accurate automatic sleep stage classification in a clinical paediatric population
por: Somaskandhan, P, et al.
Publicado: (2021) -
STAR sleep recording export software for automatic export and anonymization of sleep studies
por: Nikkonen, Sami, et al.
Publicado: (2022) -
P113 A detailed analysis of multicentric sleep staging inter-rater variabilities
por: Somaskandhan, P, et al.
Publicado: (2022) -
Severe desaturations increase psychomotor vigilance task-based median reaction time and number of lapses in obstructive sleep apnoea patients
por: Kainulainen, Samu, et al.
Publicado: (2020) -
P020 Reduced duration and continuity of N3 sleep is associated with excessive daytime sleepiness in suspected obstructive sleep apnea patients
por: Chen, X, et al.
Publicado: (2021)