Neural network in modeling glucose-insulin behavior

In this paper we propose a neural network identification of a mathematical model called MINMOD, which describes the interactions between glucose and insulin in human subjects, in order to realize an adequate model for patients suffering from {\it Diabetes Mellitus} Type 2. The model has been tested on the basis of clinical data and it can correctly reproduce glucose and insulin reply and temporal evolution, according to experimental data test. Using neural networks, we can predict the glucose temporal evolution without invasive technique for patients, with the aim to determine the clinical effects to be made in case of pathological behaviors