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Issue title: Some highlights on fuzzy systems and data mining
Guest editors: Shilei Sun, Silviu Ionita, Eva Volná, Andrey Gavrilov and Feng Liu
Article type: Research Article
Authors: Choi, Hyemia | Han, Kyungsooa | Choi, Kyounghob | Ahn, Jeongyonga; *
Affiliations: [a] Department of Statistics (Institute of Applied Statistics), Chonbuk National University, Korea | [b] Department of Basic Medical Science, Jeonju University, Korea
Correspondence: [*] Corresponding author. Jeongyong Ahn, Department of Statistics (Institute of Applied Statistics), Chonbuk National University, Korea. Tel.: +82 63 270 3392; Fax: +82 63 270 3405; E-mail: [email protected].
Abstract: For medical diagnosis based on fuzzy relations of diseases and symptoms, max-min composition method and distance-based method are frequently used. However, they often lead to diagnostic confusion and puzzle due to their different results. In this paper, we suggest a new method for medical diagnosis using the quantiles of the measures used in both methods to avoid such problems. As an illustration of usefulness, the proposed method is applied to medical diagnosis of headache. The results of the simulation show that the two methods with the normal measures have significant difference in headache diagnosis, while the difference decreases when the quantiles of the normal measures are used as a diagnostic measure.
Keywords: Distance measure, fuzzy relations, max-min composition, medical diagnosis, quantile
DOI: 10.3233/JIFS-169205
Journal: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 6, pp. 3197-3202, 2016
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