Forecasting patient's behavior: a qualitative-fuzzy approach.

by R. Bellazzi, L. Ironi, R. Guglielmann, M. Stefanelli



in: P. Borne, M. Ksouri, A. El Kamel (eds.), Proc. CESA98, IMACS-IEEE Multiconference, 4, (1998), 328-333.

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.


  • Download Postscript file.
  • Back to publication list

    Liliana Ironi 1998