Comput. Biol. Med. - A differential evolution based approach for estimating minimal model parameters from IVGTT data.

Tópicos

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Resumo

Estimation of insulin sensitivity plays a crucial role in the diagnosis and clinical investigation of glucose related diseases. The Bergman minimal model provides a non-invasive approach for estimating insulin sensitivity from the glucose insulin time series data of intravenous glucose tolerance test (IVGTT). However, quite often in the traditional gradient based techniques for deriving insulin sensitivity from the minimal model, improper initialization leads to convergence problems and results in final solution, which are either incorrect or physiologically not feasible. This paper deals with a differential evolution-based approach for the determination of insulin sensitivity from the minimal model using clinical test data. Being a direct search based technique, the proposed approach enables the determination of the global solution irrespective of the initial parameter values. The fitting performance of the model with parameters estimated from the proposed approach is found to be higher than the corresponding model estimated from the widely used gradient based approach. A high correlation coefficient of 0.964 (95% confidence interval of [0.897,0.988]) is acheived between the estimated insulin sensitivity and the one obtained from the population based approach for 16 subjects. The high correlation signifies the relative similarity between the two estimated indices in representing the same physiological phenomena. The simulation results and statistical analysis reveal that the proposed technique provides a reliable estimate of insulin sensitivity with minimum prior knowledge.

Resumo Limpo

estim insulin sensit play crucial role diagnosi clinic investig glucos relat diseas bergman minim model provid noninvas approach estim insulin sensit glucos insulin time seri data intraven glucos toler test ivgtt howev quit often tradit gradient base techniqu deriv insulin sensit minim model improp initi lead converg problem result final solut either incorrect physiolog feasibl paper deal differenti evolutionbas approach determin insulin sensit minim model use clinic test data direct search base techniqu propos approach enabl determin global solut irrespect initi paramet valu fit perform model paramet estim propos approach found higher correspond model estim wide use gradient base approach high correl coeffici confid interv acheiv estim insulin sensit one obtain popul base approach subject high correl signifi relat similar two estim indic repres physiolog phenomena simul result statist analysi reveal propos techniqu provid reliabl estim insulin sensit minimum prior knowledg

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