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Visually guided classification trees for analyzing chronic patients

Authors

Cristina Soguero-Ruiz, Inmaculada Mora-Jiménez, Miguel A. Mohedano-Munoz, Manuel Rubio-Sanchez, Pablo de Miguel-Bohoyo and Alberto Sanchez

Journal Paper

https://doi.org/10.1186/s12859-020-3359-3

Publisher URL

https://bmcbioinformatics.biomedcentral.com/

Publication date

March 2020

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.