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Decision Making in Medical Diagnosis via Distance Measures on Interval Valued Fuzzy Sets

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  • Palash Dutta

    (Dibrugarh University, Assam, India)

Abstract

The uncertain and sometimes vague, imprecise nature of medical documentation and information make the field of medical diagnosis is the most important and interesting area for applications of fuzzy set theory (FST), intuitionistic fuzzy set (IFS) and interval valued fuzzy set (IVFS). In this present study, first resemblance between IFS and IVFS has been established along with reviewed some existing distance measures for IFSs. Later, an attempt has been made to derive distance measures for IVFSs from IFSs and establish some properties on distance measures of IVFSs. Finally, medical diagnosis has been carried out and exhibits the techniques with a case study under this setting.

Suggested Citation

  • Palash Dutta, 2017. "Decision Making in Medical Diagnosis via Distance Measures on Interval Valued Fuzzy Sets," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 6(4), pages 63-83, October.
    • Handle: RePEc:igg:jsda00:v:6:y:2017:i:4:p:63-83
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    Cited by:

    1. Sundarakumar M. R. & Mahadevan G. & Ramasubbareddy Somula & Sankar Sennan & Bharat S. Rawal, 2021. "An Approach in Big Data Analytics to Improve the Velocity of Unstructured Data Using MapReduce," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 10(4), pages 1-25, October.

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