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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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| Foilsithe in: | PLoS One |
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| Main Authors: | , , |
| Formáid: | Artigo |
| Teanga: | Inglês |
| Foilsithe: |
Public Library of Science
2019
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| Ábhair: | |
| Rochtain Ar Líne: | 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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