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Unsupervised phenotyping of Severe Asthma Research Program participants using expanded lung data
BACKGROUND: Previous studies have identified asthma phenotypes based on small numbers of clinical, physiologic or inflammatory characteristics. However, no studies have utilized a wide range of variables using machine learning approaches. OBJECTIVES: To identify subphenotypes of asthma utilizing blo...
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| Main Authors: | , , , , , , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2014
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4038417/ https://ncbi.nlm.nih.gov/pubmed/24589344 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jaci.2013.11.042 |
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