Research Article

Fuzzy Diagnosis Procedure of the Types of Glaucoma

by  Vijay Kumar, Isha Bharti, Y. K. Sharma
journal cover
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Issue 6
Published: February 2012
Authors: Vijay Kumar, Isha Bharti, Y. K. Sharma
10.5120/ijais12-450191
PDF

Vijay Kumar, Isha Bharti, Y. K. Sharma . Fuzzy Diagnosis Procedure of the Types of Glaucoma. International Journal of Applied Information Systems. 1, 6 (February 2012), 42-45. DOI=10.5120/ijais12-450191

                        @article{ 10.5120/ijais12-450191,
                        author  = { Vijay Kumar,Isha Bharti,Y. K. Sharma },
                        title   = { Fuzzy Diagnosis Procedure of the Types of Glaucoma },
                        journal = { International Journal of Applied Information Systems },
                        year    = { 2012 },
                        volume  = { 1 },
                        number  = { 6 },
                        pages   = { 42-45 },
                        doi     = { 10.5120/ijais12-450191 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2012
                        %A Vijay Kumar
                        %A Isha Bharti
                        %A Y. K. Sharma
                        %T Fuzzy Diagnosis Procedure of the Types of Glaucoma%T 
                        %J International Journal of Applied Information Systems
                        %V 1
                        %N 6
                        %P 42-45
                        %R 10.5120/ijais12-450191
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we propose a fuzzy method for the diagnosis of the types of glaucoma. This method is based on the relations between the symptoms and diseases by intuitionistic fuzzy sets (IFS). For this purpose, we develop a hypothetical medical information with assigned degree of membership and degree of non-membership based on the relation between symptoms and various types of glaucoma.

References
  • Adlassnig K.P. Fuzzy set theory in medical diagnosis. IEEE Transactions on Systems, Man, and Cybernetics SMC 1986; vol.16: 260-265.
  • Ahn J.Y., Kim Y.H. , Mun K.S. , S.Y. Oh, B.S Han. A fuzzy method for diagnosis of headache. IEICE Trans. INF. & SYST.; E.
  • Ahn J.Y., Kim Y.H., Kim S.K.. A fuzzy differential diagnosis of headache applying linear regression method and fuzzy classification. IEICE Trans. INF. & SYST. 2003; E86-D: 2790-2793.
  • Atanassov K. Intuitionistic fuzzy sets. Fuzzy Sets and Systems; 20: 87-96.
  • Atanassov K. Intuitionistic Fuzzy Sets: Theory and Applications. Physica -Verlag.; 63.
  • Biswas R. Intuitionistic fuzzy relations. Bull. Sous. Ens. Flous. Appl. (BUSEFAL) 1986; 70: 22-29.
  • Kumar S., Biswas R., Roy A.R.. An application of intuitionistic fuzzy sets in medical diagnosis. Fuzzy Sets and Systems 2001; 117: 209-213.
  • Losch Breton . Appl. of Fuzzy Sets to the Diagnosis of Glaucoma. 18th Ann. Intel. Conf. of the IEEE Engg. in Medicine and Biology Society, Amsterdam 1997.
  • Szmidt E., Kacprzyk J.. A measure for Intuitionistic Fuzzy Sets. Fuzzy sets and systems 2003; 121.
  • Yao J.F, Yao J.S.. Fuzzy decision making for medical diagnosis based on fuzzy number and compositional rule of inference. Fuzzy Sets and Systems 2001; 120: 351-366.
Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Intuitionistic fuzzy sets(IFS) Fuzzy relations Medical information.

Powered by PhDFocusTM