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: Wu, Wei, Bleecker, Eugene, Moore, Wendy, Busse, William W., Castro, Mario, Chung, Kian Fan, Calhoun, William J., Erzurum, Serpil, Gaston, Benjamin, Israel, Elliot, Curran-Everett, Douglas, Wenzel, Sally E.
Format: Artigo
Jezik:Inglês
Izdano: 2014
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Article
Online dostop: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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