Forecasting patient's behavior: a qualitative-fuzzy approach
by R. Bellazzi, L. Ironi, R. Guglielmann, M. Stefanelli
Proc. CESA98, IMACS-IEEE Multiconference
ABSTRACT
This paper describes the results of a novel approach for the
identification of non-linear system dynamics when applied to the Blood
Glucose metabolic system in insulin dependent diabetic patients. Such
a method is based on fuzzy systems and qualitative models: the
outcomes obtained from the simulation of a set of qualitative
differential equations are used to automatically encode the available
knowledge in a fuzzy rule-based system, which is then tuned to a set
of experimental data. The results obtained show that the proposed
framework can be reliably and efficiently used to forecast the Blood
Glucose Level dynamics in response to different perturbations.
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