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A new medical diagnosis method based on Z-numbers

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Abstract

Handling uncertainty in medical diagnoses is an open issue. In this paper, we present a new decision-making methodology based on Z-numbers. First, experts’ opinions are represented by Z-numbers. A Z-number is an ordered pair of fuzzy numbers denoted by Z = (A, B). We then propose a new method for ranking fuzzy numbers. Based on this ranking method, we present a novel method for transforming Z-numbers into basic probability assignments. This allows information from different sources to be combined by Dempster’s combination rule, and results in more reasonable decision making because of the advantages of information fusion. Finally, two experiments on risk analysis and medical diagnosis illustrate the efficiency of the proposed methodology.

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Acknowledgements

The authors greatly appreciate the reviewers’ suggestions and the editors’ encouragement. This work is partially supported by the National Natural Science Foundation of China (Grant No. 61671384), the Natural Science Basic Research Plan in Shaanxi Province of China (Program No. 2016JM6018), the Aviation Science Foundation (Program No. 20165553036), and the Fund of SAST (Program No. SAST2016083).

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Authors and Affiliations

  1. School of Electronics and Information, Northwestern Polytechnical University, Xi’an, Shaanxi, 710072, China

    Dong Wu, Feng Xue, Yehang Shou & Wen Jiang

  2. Infrared Detection Technology Research, Development Center, Shanghai Institute of Spaceflight Control Technology, CASC, Shanghai, China

    Xiang Liu & Hanqing Zheng

  3. Shanghai Institute of Spaceflight Control Technology, Shanghai, 200233, China

    Xiang Liu

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  1. Dong Wu
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Correspondence to Wen Jiang.

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Wu, D., Liu, X., Xue, F. et al. A new medical diagnosis method based on Z-numbers. Appl Intell 48, 854–867 (2018). https://doi.org/10.1007/s10489-017-1002-4

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