Medical Pattern Recognition: Applying an Improved Intuitionistic Fuzzy Cross-Entropy Approach

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 use...

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Main Author: Kuo-Chen Hung
Format: Article
Language:English
Published: Wiley 2012-01-01
Series:Advances in Fuzzy Systems
Online Access:http://dx.doi.org/10.1155/2012/863549
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author Kuo-Chen Hung
author_facet Kuo-Chen Hung
author_sort Kuo-Chen Hung
collection DOAJ
description 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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series Advances in Fuzzy Systems
spelling doaj-art-e87c651c903249b2ae3f1bd3620c71272025-02-03T07:24:39ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2012-01-01201210.1155/2012/863549863549Medical Pattern Recognition: Applying an Improved Intuitionistic Fuzzy Cross-Entropy ApproachKuo-Chen Hung0Department of Logistics Management, National Defense University, No. 70, Section 2, Jhongyang N. Road, Beitou District, Taipei City 112, TaiwanOne 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.http://dx.doi.org/10.1155/2012/863549
spellingShingle Kuo-Chen Hung
Medical Pattern Recognition: Applying an Improved Intuitionistic Fuzzy Cross-Entropy Approach
Advances in Fuzzy Systems
title Medical Pattern Recognition: Applying an Improved Intuitionistic Fuzzy Cross-Entropy Approach
title_full Medical Pattern Recognition: Applying an Improved Intuitionistic Fuzzy Cross-Entropy Approach
title_fullStr Medical Pattern Recognition: Applying an Improved Intuitionistic Fuzzy Cross-Entropy Approach
title_full_unstemmed Medical Pattern Recognition: Applying an Improved Intuitionistic Fuzzy Cross-Entropy Approach
title_short Medical Pattern Recognition: Applying an Improved Intuitionistic Fuzzy Cross-Entropy Approach
title_sort medical pattern recognition applying an improved intuitionistic fuzzy cross entropy approach
url http://dx.doi.org/10.1155/2012/863549
work_keys_str_mv AT kuochenhung medicalpatternrecognitionapplyinganimprovedintuitionisticfuzzycrossentropyapproach