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Diagnostic Rule Extraction Using the Dempster-Shafer Theory Extended for Fuzzy Focal Elements

机译:使用Dempster-Shafer理论延长模糊焦点元素的诊断规则提取

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The Dempster-Shafer theory along with the fuzzy set theory are suitable tools for the medical diagnosis support. They can deal with medical knowledge uncertainty and data imprecision. This paper presents a study of medical knowledge representation by means of the Dempster-Shafer theory extended with the fuzzy set theory and introduces the new rule selection algorithm. The presented method gives an opportunity of interpretable and reliable rule extraction. The method is elaborated and its performance is tested on a popular medical data set. Results show that the presented method can be useful for the knowledge engineer and diagnostician cooperation due to the simple rule base and clear inference method.
机译:Dempster-Shafer理论以及模糊集理论是适合医学诊断支持的工具。他们可以处理医学知识不确定性和数据不精确。本文通过模糊集理论延伸的Deppster-Shafer理论介绍了医学知识表示的研究,并引入了新的规则选择算法。本方法给出了可解释和可靠的规则提取的机会。该方法被阐述,其性能在流行的医疗数据集上进行测试。结果表明,由于简单的规则基础和清除推理方法,所呈现的方法可用于知识工程师和诊断人员合作。

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