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Challenges in Identifying Asthma Subgroups Using Unsupervised Statistical Learning Techniques
Rationale: Unsupervised statistical learning techniques, such as exploratory factor analysis (EFA) and hierarchical clustering (HC), have been used to identify asthma phenotypes, with partly consistent results. Some of the inconsistency is caused by the variable selection and demographic and clinica...
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| 主要な著者: | , , , , , , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
American Thoracic Society
2013
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3919072/ https://ncbi.nlm.nih.gov/pubmed/24180417 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1164/rccm.201304-0694OC |
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