Medical expert system with elastic fuzzy logic

H. C. Tseng, D.W. Teo
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引用次数: 17

Abstract

We investigate the use of elastic fuzzy logic in a typical medical diagnosis. Fuzzy rules are formulated using common symptoms as antecedents and diagnoses as consequents. Different weighting factors on antecedents are assigned in each rule. This is done to better reflect the fact that in most diagnoses, there are major symptoms among all related symptoms. We also formulated a geometry-mean fuzzification scheme in issuing final decisions. A multiple-pass interactive scheme to retrieve symptom descriptions from patients is used to capture more realistic diagnosis information. An internal medicine expert system with the proposed framework is used to illustrate our design.<>
基于弹性模糊逻辑的医学专家系统
我们研究了弹性模糊逻辑在典型医学诊断中的应用。模糊规则是用常见症状作为前因由和诊断作为结果来制定的。每条规则对先行词赋予不同的权重因子。这样做是为了更好地反映这样一个事实,即在大多数诊断中,在所有相关症状中都有主要症状。我们还制定了一个几何均值模糊化方案来发布最终决策。使用多通道交互方案检索患者的症状描述,以获取更真实的诊断信息。最后,用该框架设计了一个内科专家系统。
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