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SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach

Electroencephalogram (EEG) is a common base signal used to monitor brain activities and diagnose sleep disorders. Manual sleep stage scoring is a time-consuming task for sleep experts and is limited by inter-rater reliability. In this paper, we propose an automatic sleep stage annotation method call...

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Bibliografische gegevens
Gepubliceerd in:PLoS One
Hoofdauteurs: Mousavi, Sajad, Afghah, Fatemeh, Acharya, U. Rajendra
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: Public Library of Science 2019
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Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6504038/
https://ncbi.nlm.nih.gov/pubmed/31063501
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0216456
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