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Statistical and Multivariate Analysis Applied to a Database of Patients with Type-2 Diabetes

  • Diana CanalesEmail author
  • Neil Hernandez-GressEmail author
  • Ram AkellaEmail author
  • Ivan PerezEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10862)

Abstract

The prevalence of type 2 Diabetes Mellitus (T2DM) has reached critical proportions globally over the past few years. Diabetes can cause devastating personal suffering and its treatment represents a major economic burden for every country around the world. To property guide effective actions and measures, the present study aims to examine the profile of the diabetic population in Mexico. We used the Karhunen-Loève transform which is a form of principal component analysis, to identify the factors that contribute to T2DM. The results revealed a unique profile of patients who cannot control this disease. Results also demonstrated that compared to young patients, old patients tend to have better glycemic control. Statistical analysis reveals patient profiles and their health results and identify the variables that measure overlapping health issues as reported in the database (i.e. collinearity).

Keywords

Type 2 diabetes mellitus Statistical analysis Multivariate analysis Principal component analysis Dimensionality reduction Data science Data mining 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Tecnologico de MonterreyMexico CityMexico

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