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Issue:Intuitionistic fuzzy sets in some medical applications: Difference between revisions

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  | issue          = [[Notes on Intuitionistic Fuzzy Sets/07/1|"Notes on IFS", Volume 7 (2001) Number 1]], pages 1-3
  | issue          = [[Notes on Intuitionistic Fuzzy Sets/07/4|"Notes on IFS", Volume 7 (2001) Number 4]], pages 58-64
  | file            = NIFS-07-1-01-03.pdf
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[[Intuitionistic fuzzy sets]] as a generalization of [[fuzzy sets]] can be useful in situations when description of a problem by a (fuzzy) linguistic variable, given in terms of a [[membership function]] only, seems too rough. For example, in [[decision making]] problems, particularly in the case of medial diagnosis, sales analysis, new product marketing, financial services, etc. there is a fair chance of the existence of a non-null hesitation part at each moment of evaluation of an unknown object. To be more precise - intuitionistic fuzzy sets let us express e.g., the fact that the temperature of a patient changes, and other symptoms are not quite clear.  
[[Intuitionistic fuzzy sets]] as a generalization of [[fuzzy sets]] can be useful in situations when description of a problem by a (fuzzy) linguistic variable, given in terms of a [[membership function]] only, seems too rough. For example, in [[decision making]] problems, particularly in the case of medial diagnosis, sales analysis, new product marketing, financial services, etc. there is a fair chance of the existence of a non-null hesitation part at each moment of evaluation of an unknown object. To be more precise - intuitionistic fuzzy sets let us express e.g., the fact that the temperature of a patient changes, and other symptoms are not quite clear.  

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Title of paper: Intuitionistic fuzzy sets in some medical applications
Author(s):
Eulalia Szmidt
Systems Research lnstitute - Polish Academy of Sciences, ul. Newelska 6, OL-447 Warsaw, Poland
szmidt@ibspan.waw.pl
Janusz Kacprzyk
Systems Research lnstitute - Polish Academy of Sciences, ul. Newelska 6, OL-447 Warsaw, Poland
kacprzyk@ibspan.waw.pl
Published in: "Notes on IFS", Volume 7 (2001) Number 4, pages 58-64
Download:  PDF (155  Kb, File info)
Abstract: Intuitionistic fuzzy sets as a generalization of fuzzy sets can be useful in situations when description of a problem by a (fuzzy) linguistic variable, given in terms of a membership function only, seems too rough. For example, in decision making problems, particularly in the case of medial diagnosis, sales analysis, new product marketing, financial services, etc. there is a fair chance of the existence of a non-null hesitation part at each moment of evaluation of an unknown object. To be more precise - intuitionistic fuzzy sets let us express e.g., the fact that the temperature of a patient changes, and other symptoms are not quite clear.

In this article we will present intuitionistic fuzzy sets as a tool for reasoning in the presence of imperfect facts and imprecise knowledge. An example of medical diagnosis will be presented assuming there is a database, i.e. description of a set of symptoms S, and a set of diagnoses D. We will describe a state of a patient knowing results of his/her medical tests. Description of the problem uses the notion of an intuitionistic fuzzy set. The proposed method of diagnosis involves intuitionistic fuzzy distances.

Keywords: Intuitionistic fuzzy sets, Medical diagnostics
References:
  1. Atanassov K. (1986) Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20 (1986) 87-96.
  2. Atanassov K. (1999) Intuitionistic Fuzzy Sets: Theory and Applications. Physica-Verlag.
  3. Biswas R. (1997) Intuitionistic fuzzy relations. Bull. Sous. Ens. Flous.Appl. (BUSEFAL), Vol. 70, pp. 22{29.
  4. De S.K., Biswas R. and Roy A.R. (2001) An application of intuitionistic fuzzy sets in medical diagnosis. Fuzzy Sets and Systems, Vol. 117, No.2, pp. 209 - 213.
  5. Sanchez E. (1977) Solutions in composite fuzzy relation equation. Application to medical diagnosis Brouwerian Logic. In: M.M. Gupta, G.N. Saridis, B.R. Gaines (Eds.), Fuzzy Automata and Decision Process, Elsevier, North-Holland.
  6. Sanchez E. (1976) Resolution of composition fuzzy relation equations. Inform. Control, Vol. 30, pp. 38{48.
  7. Szmidt E. and Kacprzyk J. (1997) On measuring distances between intuitionistic fuzzy sets, Notes on IFS, Vol.3, No.4, pp.1 - 13.
  8. Szmidt E. and J. Kacprzyk J. (2000) Distances between intuitionistic fuzzy sets, Fuzzy Sets and Systems, Vol.114, No.3, pp.505 - 518.
  9. Zadeh L.A. (1965) Fuzzy sets. Information and Control 8, pp. 338 - 353.
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