http://www.cnr.it/ontology/cnr/individuo/prodotto/ID30525
Identification of a model of non-esterified fatty acids dynamics through genetic algorithms: The case of women with a history of gestational diabetes (Articolo in rivista)
- Type
- Label
- Identification of a model of non-esterified fatty acids dynamics through genetic algorithms: The case of women with a history of gestational diabetes (Articolo in rivista) (literal)
- Anno
- 2011-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1016/j.compbiomed.2011.01.004 (literal)
- Alternative label
Morbiducci, U.;Benedetto, G.;Kautzky-Willer, A.;Deriu, M.;Pacini, G.;Tura, A., (2011)
Identification of a model of non-esterified fatty acids dynamics through genetic algorithms: The case of women with a history of gestational diabetes
in Computers in biology and medicine
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Morbiducci, U.;Benedetto, G.;Kautzky-Willer, A.;Deriu, M.;Pacini, G.;Tura, A., (literal)
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- http://www.ncbi.nlm.nih.gov/pubmed/21333978 (literal)
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- 1, 2, 4: Department of Mechanics, Politecnico di Torino, Turin, Italy;
3: Clinic of Internal Medicine III, Medical University of Vienna, Austria;
5, 6: Metabolic Unit, Institute of Biomedical Engineering, CNR, Padova, Italy (literal)
- Titolo
- Identification of a model of non-esterified fatty acids dynamics through genetic algorithms: The case of women with a history of gestational diabetes (literal)
- 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. (C) 2011 Elsevier Ltd. All rights reserved. (literal)
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