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

Arch Med Res. 2018 Apr;49(3):213-215. doi: 10.1016/j.arcmed.2018.08.005. Epub 2018 Aug 14.

Abstract

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.

Keywords: Classification; Data mining; Diabetes mellitus; Endocrine disease; Information analysis.

MeSH terms

  • Algorithms
  • Biomarkers / analysis*
  • Cluster Analysis
  • Data Mining / methods*
  • Endocrine System Diseases / diagnosis*
  • Humans

Substances

  • Biomarkers