摘要：AbstractMathematical models of biomedical systems often have a high number of uncertain parameters that are difficult or even impossible to estimate precisely. In order to be able to adequately describe the system, it must be known how large the influence of which factors is on the model behavior and how uncertainties in the parameters affect the model accuracy. Sensitivity analysis (SA) offers a possibility to examine to what extent the variance of the model output can be described by the variability of the input factors. In this paper, a multi-step SA is fulfilled for a unified model of glucose-insulin metabolism that consists of an Elementary Effects Test for screening purposes, a functional principal component analysis for dimensionality reduction of the model output variance and a variance-based approach to determine the sensitivity indices. The concept is tested on several scenarios for type 1 and type 2 diabetic patients, as well as non-diabetics. Results show that parameters are of different importance, depending on the type and scenario studied, which should be considered in a further system analysis.
关键词：KeywordsDiabetes mellitussensitivity analysisfunctional principal componentsEETVBSA
