Rough Sets and Fuzzy Sets Theory Applied to the Sequential Medical Diagnosis

  • Andrzej Zolnierek
  • Marek Kurzynski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4774)


Sequential classification task is typical in medical diagnosis, when the investigations of the patient’s state are repeated several times. Such situation always takes place in the controlling of the drug therapy efficacy. A specific feature of this diagnosis task is the dependence between patient’s states at particular instants, which should be taken into account in sequential diagnosis algorithms. In this paper methods for performing sequential diagnosis using fuzzy sets and rough sets theory are developed and evaluated. For both soft methodologies several algorithms are proposed which differ in kind of input data and in details of classification procedures for particular instants of decision process. Proposed algorithms were practically applied to the computer-aided medical problem of recognition of patient’s acid-base equilibrium states. Results of comparative experimental analysis of investigated algorithms in respect of classification accuracy are also presented and discussed.


Fuzzy Rule Triangular Fuzzy Number Decision Algorithm Fuzzy Relation Decision Attribute 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Czogala, E., Leski, J.: Fuzzy and neuro-fuzzy intelligent systems. Springer, New York (2000)zbMATHGoogle Scholar
  2. 2.
    Dinola, A., Pedrycz, W., Sessa, S.: Fuzzy relation equations theory as a basis of fuzzy modelling: an overview. Fuzzy Sets and Systems 40, 415–429 (1991)CrossRefMathSciNetGoogle Scholar
  3. 3.
    Fang, J., Grzymala-Busse, J.: Leukemia Prediction from Gene Expression Data-a Rough Set Approach. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds.) Artificial Intelligence and Soft Computing, pp. 899–908. Springer, New York (2006)CrossRefGoogle Scholar
  4. 4.
    Goldberg, D.: Genetic algorithms in search, optimization and machine learning. Addison-Wesley, New York (1989)zbMATHGoogle Scholar
  5. 5.
    Grzymala-Busse, J.: A System for Learning from Examples Based on Rough Sets. In: Slowinski, R. (ed.) Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory, pp. 3–18. Kluwer Academic Publishers, Dordrecht (1992)Google Scholar
  6. 6.
    Kurzynski, M.: Multistage diagnosis of myocardial infraction using a fuzzy relation. LNCS (LNAI), pp. 1014–1019. Springer, New York (2004)Google Scholar
  7. 7.
    Kurzynski, M., Zolnierek, A.: Sequential Classification via Fuzzy Relations. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds.) Artificial Intelligence and Soft Computing, pp. 623–632. Springer, New York (2006)CrossRefGoogle Scholar
  8. 8.
    Michalewicz, Z.: Genetic Algorithms + Data Structure = Evolution Programs. Springer, New York (1996)Google Scholar
  9. 9.
    Pawlak, Z.: Rough Sets - Theoretical Aspect of Reasoning About Data. Kluwer Academic Publishers, Dordrecht (1991)Google Scholar
  10. 10.
    Pawlak, Z.: Rough Sets, Decision Algorithms and Bayes’ Theorem. European Journal of Operational Research 136, 181–189 (2002)zbMATHCrossRefMathSciNetGoogle Scholar
  11. 11.
    Pedrycz, W.: Fuzzy Sets in Pattern Recognition: Methodology and Methods. Pattern Recognition 23, 121–146 (1990)CrossRefGoogle Scholar
  12. 12.
    Pedrycz, W.: Genetic Algorithms for Learning in Fuzzy Relation Structures. Fuzzy Sets and Systems 69, 37–45 (1995)CrossRefGoogle Scholar
  13. 13.
    Ray, K., Dinda, T.: Pattern classification using fuzzy relational calculus. IEEE Transactions on Systems, Man and Cybernetics 33(1), 1–16 (2003)Google Scholar
  14. 14.
    Setnes, M., Babuska, R.: Fuzzy relational classifier trained by fuzzy clustering. IEEE Transactions on Systems, Man and Cybernetics 29, 619–625 (1999)CrossRefGoogle Scholar
  15. 15.
    Wang, L.X., Mendel, J.M.: Generating fuzzy rules by learning from examples. IEEE Trans. on Systems, Man and Cybernetics 22, 1414–1427 (1992)CrossRefMathSciNetGoogle Scholar
  16. 16.
    Wang, L.X.: A course in fuzzy systems and control. Prentice-Hall, New York (1998)Google Scholar
  17. 17.
    Zolnierek, A.: Application of rough sets theory to the sequential diagnosis. In: Maglaveras, N., Chouvarda, I., Koutkias, V., Brause, R. (eds.) ISBMDA 2006. LNCS (LNBI), vol. 4345, pp. 413–422. Springer, Heidelberg (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Andrzej Zolnierek
    • 1
  • Marek Kurzynski
    • 1
  1. 1.Wroclaw University of Technology, Faculty of Electronics, Chair of Systems and Computer Networks, Wyb. Wyspianskiego 27, 50-370 WroclawPoland

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