A New Medical Diagnosis Method Based on Z-Numbers
May 07, 2017 Β· Declared Dead Β· π Applied intelligence (Boston)
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Authors
Dong Wu, Xiang Liu, Feng Xue, Hanqing Zheng, Yehang Shou, Wen Jiang
arXiv ID
1705.02620
Category
cs.AI: Artificial Intelligence
Citations
34
Venue
Applied intelligence (Boston)
Last Checked
4 months ago
Abstract
How to handle uncertainty in medical diagnosis is an open issue. In this paper, a new decision making methodology based on Z-numbers is presented. Firstly, the experts' opinions are represented by Z-numbers. Z-number is an ordered pair of fuzzy numbers denoted as Z = (A, B). Then, a new method for ranking fuzzy numbers is proposed. And based on the proposed fuzzy number ranking method, a novel method is presented to transform the Z-numbers into Basic Probability Assignment (BPA). As a result, the information from different sources is combined by the Dempster' combination rule. The final decision making is more reasonable due to the advantage of information fusion. Finally, two experiments, risk analysis and medical diagnosis, are illustrated to show the efficiency of the proposed methodology.
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