文献类型：期刊文献

英文题名：Multi-period medical diagnosis method using a single valued neutrosophic similarity measure based on tangent function

作者：Ye, Jun[1];Fu, Jing[2]

机构：[1]Shaoxing Univ, Dept Elect & Informat Engn, 508 Huancheng West Rd, Shaoxing 312000, Zhejiang, Peoples R China;[2]Shaoxing Second Hosp, Shaoxing 312000, Zhejiang, Peoples R China

年份：2016

卷号：123

起止页码：142

外文期刊名：COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

收录：SCI-EXPANDED(收录号：WOS:000366948400012)、、EI(收录号：20155201727674)、Scopus(收录号：2-s2.0-84951909327)、WOS

基金：This paper was supported by the National Natural Science Foundation of China (No. 71471172).

语种：英文

外文关键词：Neutrosophic set; Single valued neutrosophic set; Similarity measure; Tangent function; Multi-period medical diagnosis

外文摘要：Because of the increased volume of information available to physicians from advanced medical technology, the obtained information of each symptom with respect to a disease may contain truth, falsity and indeterminacy information. Since a single-valued neutrosophic set (SVNS) consists of the three terms like the truth-membership, indeterminacy-membership and falsity-membership functions, it is very suitable for representing indeterminate and inconsistent information. Then, similarity measure plays an important role in pattern recognition and medical diagnosis. However, existing medical diagnosis methods can only handle the single period medical diagnosis problem, but cannot deal with the multi-period medical diagnosis problems with neutrosophic information. Hence, the purpose of this paper was to propose similarity measures between SVNSs based on tangent function and a multi-period medical diagnosis method based on the similarity measure and the weighted aggregation of multi-period information to solve multi-period medical diagnosis problems with single-valued neutrosophic information. Then, we compared the tangent similarity measures of SVNSs with existing similarity measures of SVNSs by a numerical example about pattern recognitions to indicate the effectiveness and rationality of the proposed similarity measures. In the multi-period medical diagnosis method, we can find a proper diagnosis for a patient by the proposed similarity measure between the symptoms and the considered diseases represented by SVNSs and the weighted aggregation of multi-period information. Then, a multi-period medical diagnosis example was presented to demonstrate the application of the proposed diagnosis method and to indicate the effectiveness of the proposed diagnosis method by the comparative analysis. The diagnosis results showed that the developed multi-period medical diagnosis method can help doctors make a proper diagnosis by the comprehensive information of multi-periods. (C) 2015 Elsevier Ireland Ltd. All rights reserved.