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Expert-level sleep scoring with deep neural networks
OBJECTIVES: Scoring laboratory polysomnography (PSG) data remains a manual task of visually annotating 3 primary categories: sleep stages, sleep disordered breathing, and limb movements. Attempts to automate this process have been hampered by the complexity of PSG signals and physiological heterogen...
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| Опубликовано в: : | J Am Med Inform Assoc |
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| Главные авторы: | , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Oxford University Press
2018
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6289549/ https://ncbi.nlm.nih.gov/pubmed/30445569 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamia/ocy131 |
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