English

Estimation and svm classification of glucose-insulin model parameters from OGTT data. An aid for diabetes diagnostics

Applications 2017-11-27 v1

Abstract

In the Oral Glucose Tolerance Test (OGTT), a patient, after an overnight fast ingests a load of glucose. Then measurements of glucose concentration are taken every 30 minutes during two hours. The test is used to aid diagnosis of diabetes, namely, type 2 diabetes mellitus and glucose intolerance. Several mathematical models have been introduced to describe the glucose-insulin system during an OGTT. Models consist on systems of differential equations where most parameters are unknown. Estimation of these parameters is an aim of this work. In a minimal model, two of such parameters are proposed for classification by means of a SVM technique. Consequently, a case is made for this classification as an aid for diagnosis.

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Cite

@article{arxiv.1711.09002,
  title  = {Estimation and svm classification of glucose-insulin model parameters from OGTT data. An aid for diabetes diagnostics},
  author = {Miguel Angel Moreles and Joaquin Peña and Paola Vargas and Adriana Monroy and Silvestre Alavez},
  journal= {arXiv preprint arXiv:1711.09002},
  year   = {2017}
}

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