Identification of a model of non-esterified fatty acids dynamics through genetic algorithms: The case of women with a history of gestational diabetes

Authors:
Umberto Morbiducci;Giacomo Di Benedetto;Alexandra Kautzky-Willer;Marco A. Deriu;Giovanni Pacini;Andrea Tura
Affiliations:
Department of Mechanics, Politecnico di Torino, Turin, Italy;Department of Mechanics, Politecnico di Torino, Turin, Italy;Clinic of Internal Medicine III, Medical University of Vienna, Austria;Department of Mechanics, Politecnico di Torino, Turin, Italy;Metabolic Unit, Institute of Biomedical Engineering, CNR, Padova, Italy;Metabolic Unit, Institute of Biomedical Engineering, CNR, Padova, Italy
Venue:
Computers in Biology and Medicine
Year:
2011

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Abstract

Elevation in non-esterified fatty acids (NEFA) has been shown to modulate insulin secretion and it is considered as a risk factor for the development of type 2 diabetes. Here we present a method that complements a mathematical model of NEFA kinetics with genetic algorithms for model identification. The complemented strategy allowed to assess parameters of NEFA kinetics and to get insight into their relationship with insulin during oral glucose tolerance tests in women with former gestational diabetes: (i) providing a reliable estimation of the model parameters, (ii) assuring the usability of the model, and (iii) promoting and facilitating its application in a clinical context.