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P. Sa-Cout ; A. Todo-Bom ; J. Bousquet ;Revista Portuguesa de Pneumología 2015, 21 6

Autor: C.C. Loureiro

Fuente: http://www.redalyc.org/


Introducción



Revista Portuguesa de Pneumología ISSN: 0873-2159 sppneumologia@mail.telepac.pt Sociedade Portuguesa de Pneumologia Portugal Loureiro, C.C.; Sa-Cout, P.; Todo-Bom, A.; Bousquet, J. Cluster analysis in phenotyping a Portuguese population Revista Portuguesa de Pneumología, vol.
21, núm.
6, 2015, pp.
299-306 Sociedade Portuguesa de Pneumologia Lisboa, Portugal Available in: http:--www.redalyc.org-articulo.oa?id=169743149005 How to cite Complete issue More information about this article Journals homepage in redalyc.org Scientific Information System Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Non-profit academic project, developed under the open access initiative Document downloaded from http:--www.elsevier.pt, day 18-12-2015.
This copy is for personal use.
Any transmission of this document by any media or format is strictly prohibited. Rev Port Pneumol.
2015;21(6):299---306 www.revportpneumol.org ORIGINAL ARTICLE Cluster analysis in phenotyping a Portuguese population C.C.
Loureiro a,b,∗ , P.
Sa-Couto c , A.
Todo-Bom d,b , J.
Bousquet e,f a Pneumology Unit, Hospitais da Universidade de Coimbra, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal Centre of Pneumology, Faculty of Medicine, University of Coimbra, Portugal c Center for Research and Development in Mathematics and Applications, Department of Mathematics, University of Aveiro, Aveiro, Portugal d Immunoallergology Unit, Hospitais da Universidade de Coimbra, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal e University Hospital Arnaud de Villeneuve, Montpellier, France f Inserm, CESP Centre for Research in Epidemiology and Population Health, U1018, Respiratory and Environmental Epidemiology Team, Villejuif, France b Received 28 May 2015; accepted 17 July 2015 Available online 3 September 2015 KEYWORDS Asthma; Phenotypes; Cluster analysis Abstract Background: Unbiased cluster analysis using clinical parameters has identifie...





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