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Classification algorithms for predicting sleepiness and sleep apnea severity
Identifying predictors of subjective sleepiness and severity of sleep apnea are important yet challenging goals in sleep medicine. Classification algorithms may provide insights, especially when large data sets are available. We analyzed polysomnography and clinical features available from the Sleep...
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| Main Authors: | , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2011
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3698244/ https://ncbi.nlm.nih.gov/pubmed/21752133 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/j.1365-2869.2011.00935.x |
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