Cargando…
Inter-database validation of a deep learning approach for automatic sleep scoring
STUDY OBJECTIVES: Development of inter-database generalizable sleep staging algorithms represents a challenge due to increased data variability across different datasets. Sharing data between different centers is also a problem due to potential restrictions due to patient privacy protection. In this...
Autores principales: | Alvarez-Estevez, Diego, Rijsman, Roselyne M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8366993/ https://www.ncbi.nlm.nih.gov/pubmed/34398931 http://dx.doi.org/10.1371/journal.pone.0256111 |
Ejemplares similares
-
Computer-assisted analysis of polysomnographic recordings improves inter-scorer associated agreement and scoring times
por: Alvarez-Estevez, Diego, et al.
Publicado: (2022) -
Inter-device reliability of an automatic-scoring actigraph for measuring sleep in healthy adults
por: Driller, Matthew, et al.
Publicado: (2016) -
Automatic Human Sleep Stage Scoring Using Deep Neural Networks
por: Malafeev, Alexander, et al.
Publicado: (2018) -
SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach
por: Mousavi, Sajad, et al.
Publicado: (2019) -
Automatic Liver Viability Scoring with Deep Learning and Hyperspectral Imaging
por: Felli, Eric, et al.
Publicado: (2021)