Data Mining and Endocrine Diseases: A New Way to Classify?
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Fecha
2018-04
Autores
Salazar, Juan
Espinoza, Cristobal
Mindiola, Andres
Bermudez, Valmore
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Editor
Elsevier
Resumen
Data mining consists of using large database analysis to detect patterns, relationships and
models in order to describe (or even predict) the appearance of a future event; to accomplish
this, it uses classification methods, rules of association, regression patterns, link and
cluster analyses. Recently this approach has been used to propose a new diabetes mellitus
classification, using information analysis techniques through which the selection bias
minimally influences categorization, this new focus that includes data mining previously
implemented to predict, identify biomarkers, complications, therapies, health policies, genetic
and environmental effects of this disease; it could be generalized in the field of
endocrinology, in the classification of other endocrine diseases.
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Palabras clave
Data mining, Classification, Endocrine disease, Diabetes mellitus, Information analysis