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Data Mining and Endocrine Diseases: A New Way to Classify?

Abstract:

Data mining consists of using large database analysis to detect patterns, relationships and models in order to describe (or even pbkp_redict) 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 pbkp_redict, 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.