Learning from data through the integration of qualitative models and fuzzy systems

This paper presents a method for the identification of the dynamics of non-linear patho-physiological systems by learning from data. The key idea which underlies our approach consists in the integration of qualitative modeling methods with fuzzy logic systems. The major advantage which derives from such an integrated framework lies in its capability both to represent the structural knowledge of the system at study and to exploit the available experimental data, so that a functional approximation of the system dynamics can be determined and used as a reasonable predictor of the patient's future state. As testing ground of our method, we have considered the problem of identifying the response to the insulin therapy from insulin-dependent diabetic patients: the results obtained are presented and discussed in the paper.