Estimation and svm classification of glucose-insulin model parameters from OGTT data : an aid for diabetes diagnostics
Estimation and svm classification of glucose-insulin model parameters from OGTT data : an aid for diabetes diagnostics
Date
2017
Authors
Adriana Monroy, 0000-0003-0696-1227
Silvestre Alavez, 0000-0002-9220-0696
Journal Title
Journal ISSN
Volume Title
Publisher
Cornell University Library
Abstract
Description
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 di erential 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 classication by means of a SVM technique. Consequently, a case is made for this classi cation as an aid for diagnosis.
Keywords
MEDICINA Y CIENCIAS DE LA SALUD