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A fuzzy model of glucose regulation
1Biomedical and Electrical Engineering, University of Arkansas, Fayetteville 72701, USA.
Abstract:
We present a detailed glucose regulation model using fuzzy inference system (FIS) descriptions of hormonal control action and the familiar Michaelis-Menten (M-M) kinetic description for glucose transport. The fuzzy M-M model is compared and contrasted with a well-known comprehensive glucose model. The two models give similar results for glucose response, endogenous glucose production, and total uptake. The fuzzy M-M model features a renal subsystem that provides 25% of the endogenous glucose production. The work demonstrates the successful application of fuzzy logic and fuzzy inference to biological modelling. The flexibility of fuzzy inference, a linguistic description technique, permits conceptually simple statements about nonlinear processes.
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