Soft clustering using real-world data for the identification of multimorbidity patterns in an elderly population: Cross-sectional study in a Mediterranean population

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RECERCAT Home > Universitat Politècnica de Catalunya > Documents de recerca > View document

To access the full text documents, please follow this link: http://hdl.handle.net/2117/169036

Title:	Soft clustering using real-world data for the identification of multimorbidity patterns in an elderly population: Cross-sectional study in a Mediterranean population
Author:	Violán Fors, Concepción; Foguet Boreu, Quintí; Fernández Bertolín, Sergio; Guisado Clavero, Marina; Cabrera-Bean, Margarita; Formiga, Francesc; Valderas, José Maria; Roso Llorach, Albert
Other authors:	Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions
Abstract:	The aim of this study was to identify, with soft clustering methods, multimorbidity patterns in the electronic health records of a population =65 years, and to analyse such patterns in accordance with the different prevalence cut-off points applied. Fuzzy cluster analysis allows individuals to be linked simultaneously to multiple clusters and is more consistent with clinical experience than other approaches frequently found in the literature.
Abstract:	Peer Reviewed
Subject(s):	-Àrees temàtiques de la UPC::Ciències de la salut::Medicina::Medicina comunitària i salut pública -Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació::Bases de dades -Clinical epidemiology -Data mining -Chronic conditions -Multimorbidity -Cluster analysis -Epidemiology -Fuzzy C-Means -Epidemiologia clínica -Mineria de dades
Rights:	Attribution-NonCommercial-NoDerivs 3.0 Spain http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Document type:	Article - Published version Article
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