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Medical Pattern Recognition: Applying an Improved Intuitionistic Fuzzy Cross-Entropy Approach
Author(s) -
Kuo-Chen Hung
Publication year - 2011
Publication title -
advances in fuzzy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 19
eISSN - 1687-711X
pISSN - 1687-7101
DOI - 10.1155/2012/863549
Subject(s) - intuitionism , computer science , entropy (arrow of time) , fuzzy logic , artificial intelligence , medical diagnosis , mathematics , machine learning , medicine , physics , geometry , pathology , quantum mechanics
One of the toughest challenges in medical diagnosis is the handling of uncertainty. Since medical diagnosis with respect to the symptoms uncertain, they will be assumed to have an intuitive nature. Thus, to obtain the uncertain optimism degree of the doctor, fuzzy linguistic quantifiers will be used. The aim of this article is to provide an improved nonprobabilistic entropy approach to support doctors examining the work of the preliminary diagnosing. The proposed entropy measure is based on intuitionistic fuzzy sets, extrainformation regarding hesitation degree, and an intuitive and mathematical connection between the notions of entropy in terms of fuzziness and intuitionism has been revealed. An illustrative example for medical pattern recognition demonstrates the usefulness of this study. Furthermore, in order to make computing and ranking results easier and to increase the recruiting productivity, a computer-based interface system has been developed to support doctors in making more efficient judgments

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