1 citations · 1 across the 5 of their papers we have counts for
5 papers
Bayesian statistical models to explore the use glucometer measurements of capillary blood sugar for OGTT Tests
Nicolás Kuschinski, J. Andrés Christe, Adriana Monroy
A common test for the diagnosis of type 2 diabetes is the Oral Glucose Tolerance Test (OGTT). Recent developments in the study of OGTT tests have framed it as a Bayesian inverse pr…
A validation study of normoglycemia and dysglycemia indices as a diabetes risk model
Paola Vargas, Miguel Angel Moreles, Joaquin Peña +1
In this work, we test the performance of Peak glucose concentration () and average of glucose removal rates (), as normoglycemia and dysglycemia indices on a population monit…
Bayesian Experimental Design for Oral Glucose Tolerance Tests (OGTT)
Nicolás E. Kuschinski, J. Andrés Christen, Adriana Monroy +1
OGTT is a common test, frequently used to diagnose insulin resistance or diabetes, in which a patient's blood sugar is measured at various times over the course of a few hours. Rec…
Estimation and svm classification of glucose-insulin model parameters from OGTT data. An aid for diabetes diagnostics
Miguel Angel Moreles, Joaquin Peña, Paola Vargas +2
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 durin…
Modeling Oral Glucose Tolerance Test (OGTT) data and its Bayesian Inverse Problem
Nicolás Kuschinski, J. Andrés Christen, Adriana Monroy +1
One common way to test for diabetes is the Oral Glucose Tolerance Test or OGTT. Most common methods for the analysis of the data on this test are wasteful of much of the informatio…