Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12530/54542
Title: Visually guided classification trees for analyzing chronic patients
Authors: 
Filiation: Departamento Económico-Financiero. Hospital Universitario de Fuenlabrada
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Mesh: 
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Issue Date: 11-Mar-2020
Publisher: Springer Science and Business Media LLC
Citation: Soguero Ruiz C, Mora Jiménez I, Mohedano Muñoz MA, Rubio Sánchez M, Miguel Bohoyo P, Sánchez A. Visually guided classification trees for analyzing chronic patients. BMC Bioinformatics. 2020;21(Suppl 2):92.
Abstract: Chronic diseases are becoming more widespread each year in developed countries, mainly due to increasing life expectancy. Among them, diabetes mellitus (DM) and essential hypertension (EH) are two of the most prevalent ones. Furthermore, they can be the onset of other chronic conditions such as kidney or obstructive pulmonary diseases. The need to comprehend the factors related to such complex diseases motivates the development of interpretative and visual analysis methods, such as classification trees, which not only provide predictive models for diagnosing patients, but can also help to discover new clinical insights.
PMID: 32164533
URI: https://hdl.handle.net/20.500.12530/54542
Rights: info:eu-repo/semantics/openAccess
Appears in Collections:Hospitales > H. U. de Fuenlabrada > Artículos

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