Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/20.500.12222/147
Título : Estimation and svm classification of glucose-insulin model parameters from OGTT data : an aid for diabetes diagnostics
Autor(es) : Adriana Monroy, 0000-0003-0696-1227Silvestre Alavez, 0000-0002-9220-0696
Autor(es) sin ID: Moreles, Miguel AngelPeña, JoaquinVargas, Paola
Fecha de publicación : 2017
Tipo de resultado Científico: article
Materia o Disciplina: MEDICINA Y CIENCIAS DE LA SALUD
Palabras clave: Glucosa; Paciente; Diabetes; Diabetes mellitus; Modelos matemáticos
Descripción : 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.
Editor: Cornell University Library
URI : http://hdl.handle.net/20.500.12222/147
Condiciones de licencia: https://creativecommons.org/licenses/by-nc-nd/4.0/
Fuente: arXiv (2017)
ISSN: 2331-8422
Aparece en las colecciones: Artículos Científicos

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