Summary
In this chapter we evaluate the ability of the minimal model of glucose disappearance to describe experimental data collected from 9 diabetic patients controlled subcutaneously by an insulin pump. Two versions of the minimal model are used: the nonlinear classic minimal model developed by Bergman et al. (MM) and the linear approximation proposed by Fernandez et al. (LMM). All data windows (n = 13) show residuals that are correlated for both the LMM and MM (p-value < 0.01). The results also show that both the LMM and MM provide an equivalent goodness of fit with R 2 values that are statistically equivalent (p-value > 0.05). This study confirms that the minimal model of glucose disappearance, either the classic or linear version, is unable to describe the observed experimental data possibly as a result of the physiological constraints imposed by the minimal model approach on the system dynamics, together with possible errors derived from the unmeasured insulin dynamics. Further testing on more complex models should be performed.
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Fernandez, M., Villasana, M., Streja, D. (2009). The Minimal Model of Glucose Disappearance in Type I Diabetes. In: Sidhu, A.S., Dillon, T.S. (eds) Biomedical Data and Applications. Studies in Computational Intelligence, vol 224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02193-0_13
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DOI: https://doi.org/10.1007/978-3-642-02193-0_13
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