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Issue:A system for medical diagnosis based on intuitionistic fuzzy relation

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Title of paper: A system for medical diagnosis based on intuitionistic fuzzy relation
Author(s):
Ismat Beg
Lahore School of Economics, Lahore, Pakistan
begismat@yahoo.com
Tabasam Rashid
University of Management and Technology, Lahore, Pakistan
tabasam.rashid@gmail.com
Published in: "Notes on Intuitionistic Fuzzy Sets", Volume 21, 2015, Number 3, pages 80—89
Download:  PDF (302  Kb, File info)
Abstract: The aim of this paper is to propose a new approach for medical diagnosis by using trapezoidal valued intuitionistic fuzzy relations. First, we develop trapezoidal valued intuitionistic fuzzy relations and then use it to solve medical diagnosis decision making problem. We study Sanchez’s method of medical diagnosis with the notion of trapezoidal valued intuitionistic fuzzy sets. To further elaborate our method an example of medical diagnosis is given assuming that there is a database, i.e. description of a set of symptoms and a set of diagnoses.
Keywords: Medical diagnosis, Fuzzy set, Intuitionistic fuzzy relation.
AMS Classification: 03B52, 03E72, 46S40, 62C06, 68T37, 91B06.
References:
  1. Alayon, S., Robertson, R., Warfield, S.K., & Ruiz-Alzola, J. (2007) A fuzzy system for helping medical diagnosis of malformations of cortical development, Journal of Biomedical Informatics, 40, 221–235.
  2. Anooj, P. K. (2012) Clinical decision support system: Risk level prediction of heart disease using weighted fuzzy rules, Journal of King Saud University – Computer and Information Sciences, 24, 27–40.
  3. Ashtiani, B., Haghighirad, F., Makui, A., & Montazer, G. (2009) Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets, Applied Soft Computing, 9, 457–461.
  4. Atanassov, K. (1986) Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20, 87–96.
  5. Atanassov, K. (1994) Operators over interval-valued intuitionistic fuzzy sets, Fuzzy Sets and Systems, 64(2), 159–174.
  6. Atanassov, K., & Gargov, G. (1989) Interval-valued intuitionistic fuzzy sets, Fuzzy Sets and Systems, 31, 343–349.
  7. Beg, I., & Rashid, T. (2013) A generalized model of judgment and preference aggregation, Fuzzy Economic Review, XVIII(1), 9–27.
  8. Beg, I.,& Rashid, T. (2014) Multi-criteria trapezoidal valued intuitionistic fuzzy decision making with Choquet integral based TOPSIS, OPSEARCH, 51(1), 98–129.
  9. Boran, F.E., Gen, S., Kurt, M., & Akay, D. (2009) A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method, Expert Systems with Applications, 36, 11363–11368.
  10. Chen, T.Y., & Tsao, C.Y. (2008) The interval-valued fuzzy TOPSIS method and experimental analysis, Fuzzy Sets and Systems, 159, 1410–1428.
  11. De, S. K., Biswas R., & Roy, A. R. (2001) An application of intuitionistic fuzzy sets in medical diagnosis, Fuzzy Sets and Systems, 117, 209–213.
  12. Esogbue, A. O. (1999) Fuzzy dynamic programming, fuzzy adaptive neuro control, and the general medical diagnosis problem, Computers and Mathematics with Applications, 37, 37-45.
  13. Khalaf, M. M. (2013) Medical diagnosis via interval valued intuitionistic fuzzy sets, Annals of Fuzzy Mathematics and Informatics, 6(2) 245–249.
  14. Li, D.F. (2005) Multiattribute decision making models and methods using intuitionistic fuzzy sets, Journal of Computer and System Sciences, 70, 73–85.
  15. Li, D.F., Wang Y. C., Liu S., & Shan F. (2008) Fractional programming methodology for multi-attribute group decision making using IFS, Applied Soft Computing, 8(1), 219–225.
  16. Lin, C. T., & Chen, Y. T. (2004) Bid/no-bid decision making a novel linguistic approach, International Journal of Project Management, 22(7), 585–593.
  17. Nguyen, H.T., & Walker, E. (2006) A First Course in Fuzzy logic, third edition, Chapman & Hall/CRC Press, Boca Raton.
  18. Sanchez, E. (1976) Resolution of composition fuzzy relation equations, Information and Control, 30, 38–48.
  19. Sanchez, E. (1977) Solutions in composite fuzzy relation equation, Application to medical diagnosis in Brouwerian Logic, in: M. M. Gupta, G.N. Saridis, B.R. Gaines (Eds.), Fuzzy Automata and Decision Process, Elsevier, North-Holland.
  20. Schnatter, S. F. (1992) On statistical inference for fuzzy data with applications to descriptive statistics, Fuzzy Sets and Systems, 50, 143–165.
  21. Shannon, A., Kim, S., Kim, Y., Sorsich, J., Atanassov, K., & Georgiev, P. (1997) A possibility for implementation of elements of the intuitionistic fuzzy logic in decision making in medicine, Proceedings of the First Int. Conf. on Intuitionistic Fuzzy Sets (J. Kacprzyk and K. Atanassov, Eds.), Notes on Intuitionistic Fuzzy Sets, 3(4), 40–43.
  22. Tai, W.S., & Chen, C.T. (2009) A new evaluation model for intellectual capital based on computing with linguistic variable, Expert Systems with Applications, 36, 3483–3488.
  23. Wang, R.C., & Chuu, S.J. (2004) Group decision making using a fuzzy linguistic approach for evaluating the flexibility in a manufacturing system, European Journal of Operational Research, 154(3), 563–572.
  24. Zadeh, L. A. (1965) Fuzzy sets, Information and Control, 8, 338–356.
  25. Zhang, Q., & Luo, S. (2011) A decision making method based on weighted interval-valued fuzzy reasoning algorithm, Procedia Engineering, 15, 3093–3097.
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