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Automated sleep stage scoring of the Sleep Heart Health Study using deep neural networks
STUDY OBJECTIVES: Polysomnography (PSG) scoring is labor intensive and suffers from variability in inter- and intra-rater reliability. Automated PSG scoring has the potential to reduce the human labor costs and the variability inherent to this task. Deep learning is a form of machine learning that u...
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| Publicado no: | Sleep |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6802563/ https://ncbi.nlm.nih.gov/pubmed/31289828 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/sleep/zsz159 |
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