Universal Minimal Model for Glucose-Insulin Relationship with the Influence of Food Dynamic

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Abstract

We propose a minimal model defining the relationship between glucose and insulin with the added influence of food intakes. The constructed model consists of a system of 3 nonlinear ordinary differential equations (ODEs). The solutions of our model for both normal and diabetic subjects are compared with a minimal model and a maximal model representing the same relationship. We found that the outputs of our model are similar to those from the minimal and maximal models for both normal and diabetic subjects; the R2 are 0.9997 and 0.9922, respectively, when compared with the minimal model, and are 0.9995 and 0.9940, respectively, when compared with the maximal model. Moreover, the relative errors between solutions are at most 0.9035% and as low as 1.488×10-2% on average when compared with the minimal model for normal subjects and at most 1.331% and as low as 0.1159% on average for diabetic subjects. The discrepancy between our model and the maximal model are at most 1.590% and 5.453% for normal and diabetic subjects, respectively, with a relative error averaging 0.2138% and 0.9002% for normal and diabetic subjects, respectively.

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Kumnungkit, K., Likasiri, C., Pongvuthithum, R., & Tantakitti, F. (2022). Universal Minimal Model for Glucose-Insulin Relationship with the Influence of Food Dynamic. Computational and Mathematical Methods in Medicine, 2022. https://doi.org/10.1155/2022/8990767

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