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

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages501-512
Number of pages12
Volume1211
ISBN (Print)354062709X, 9783540627098
DOIs
Publication statusPublished - 1997
Event6th Conference on Artificial Intelligence in Medicine in Europe, AIME 1997 - Grenoble, France
Duration: Mar 23 1997Mar 26 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1211
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other6th Conference on Artificial Intelligence in Medicine in Europe, AIME 1997
CountryFrance
CityGrenoble
Period3/23/973/26/97

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Bellazzi, R., Ironi, L., Guglielmann, R., & Stefanelli, M. (1997). Learning from data through the integration of qualitative models and fuzzy systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1211, pp. 501-512). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1211). Springer Verlag. https://doi.org/10.1007/BFb0029484