Advertisement

The Choquet Integral Applied to Ranking Therapies in Radiation Cystitis

  • Elisabeth Rakus-AnderssonEmail author
  • Janusz Frey
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 323)

Abstract

We modify the classical fuzzy decision making model by adopting the concept of the Choquet integral as a measure of the therapy utility, when proving different treatments in radiation cystitis. The objective is to rank therapies as a sequence, commencing with the most efficacious remedy.

Keywords

Utility matrix parametric membership functions weights of importance utilities of therapies Choquet integral 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bouchon-Meunier, B., Jia, Y.: Linguistic modifiers and imprecise categories. Special Issue: Uncertanty Management in Knowledge-based Systems 7(1), 25–36 (1992)zbMATHGoogle Scholar
  2. 2.
    Denton, A.S., Clarke, N., Maher, J.: Non-surgical Interventions for Late Radiation Cystitis in Patients who Have Received Radical Radiotherapy to the Pelvis. Wiley Online – The Cochrane Library (2009), http://onlinelibrary.wiley.com/doi/10.1002/14651858.CD001773/pdf
  3. 3.
    Grabisch, M., Murofushi, T., Sugeno, M., Kacprzyk, J.: Fuzzy Measures and Integrals. Theory and Applications. Physica Verlag, Berlin (2000)zbMATHGoogle Scholar
  4. 4.
    Martinez-Rodrigues, R., Areal Calama, J., Buisan Rueda, O., González Satue, C., Sanchez Macias, J., Arzoz Fabregas, M., Gago Ramos, J., Bayona Arenas, S., Ibarz Servio, L., Saladié Roig, J.M.: Practical Treatment Approach of Radiation Induced Cystitis. Actas Urol Esp. 34(7), 603–609 (2010)Google Scholar
  5. 5.
    Mirofushi, T., Sugeno, M.: An Interpretation of Fuzzy Measures and the Choquet Integral as an Integral with Respect to a Fuzzy Measure. Fuzzy Sets and Systems 29, 201–227 (1989)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Novák, V., Perfilieva, I.: Evaluating of Linguistic Expressions and Functional Fuzzy Theories in Fuzzy Logic. In: Zadeh, L.A., Kacprzyk, J. (eds.) Computing with Words in Information – Intelligent Systems. STUDFUZZ, vol. 33, pp. 383–406. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  7. 7.
    Rakus-Andersson, E., Jogreus, C.: The Choquet and Sugeno Integrals as Measures of Total Effectiveness of Medicines. In: Castillo, O., Melin, P., Ross, O.M., Cruz, M., Pedrycz, W., Kacprzyk, J. (eds.) Theoretical Advances and Applications of Fuzzy Logic and Soft Computing. ASC, vol. 42, pp. 253–262. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  8. 8.
    Rakus-Andersson, E.: Decision-making Techniques in Ranking of Medicine Effectiveness. In: Sordo, M., Vaidya, W., Jain, L.C. (eds.) Advanced Computational Intelligence Paradigms in Healthcare 3. SCI, vol. 107, pp. 51–73. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  9. 9.
    Rakus-Andersson, E.: Adjusteds-parametric Functions in the Creation of Symmetric Constraints. In: Proceedings of the 10th International Conference on Intelligent Systems Design and Applications, ISDA 2010, pp. 451–456 (2010)Google Scholar
  10. 10.
    Rakus-Andersson, E.: The Mamdani Controller with Modeled Families of Constraints in Evaluation of Cancer Patient Survival Length. In: Ramanna, S., Jain, L.C., Howlett, R.J. (eds.) Emerging Paradigms in ML and Applications. SIST, vol. 13, pp. 359–378. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  11. 11.
    Rakus-Andersson, E.: Selected Algorithms of Computational Intelligence in Surgery Decision Making. Open Access book Gastroenterology in SCITECH (2012), http://www.intechopen.com/articles/show/title/selected-algorithms-of-computational-intelligence-in-cancer-surgery-decision-making
  12. 12.
    Rakus-Andersson, E., Frey, J.: α-cut Fuzzy Numbers as Utilities of Decision Making in Treatment of Radiation Cystitis. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds.) IPMU 2012, Part I. CCIS, vol. 297, pp. 140–149. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  13. 13.
    Sugeno, M.: Fuzzy Measures and Fuzzy Integrals - a Survey. In: Gupta, M.M., Saridis, G.N., Gaines, B.R. (eds.) Fuzzy Automata and Decision Processes, pp. 89–102. North-Holland, New York (1977)Google Scholar
  14. 14.
    Yager, R.R.: Fuzzy Decision Making Including Unequal Objectives. Fuzzy Sets and Systems 1, 87–95 (1978)CrossRefzbMATHGoogle Scholar
  15. 15.
    Yager, R.R.: Generalized OWA Aggregation Operators. Fuzzy Optimization and Decision Making 3, 93–107 (2004)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Mathematics and ScienceBlekinge Institute of TechnologyKarlskronaSweden
  2. 2.Department of Surgery and UrologyBlekinge County HospitalKarlskronaSweden

Personalised recommendations