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A Fuzzy Probabilistic Method for Medical Diagnosis

机译:医疗诊断的模糊概率方法

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The max-min composition in fuzzy set theory has attained reasonable success in medical diagnosis in the past thirty years for estimating the probability of a patient diagnosed with a certain disease. However, there has been no theoretical justification why the method would work. We create a theoretical model to calculate the probabilities of hypothetical patients having designated diseases, and use simulated dataset to explain why the max-min composition has been successful. In addition, based on the theoretical model, we propose a fuzzy probabilistic method to estimate the probability of a patient having a certain disease. The proposed method may produce a more accurate estimate than the max-min composition.
机译:在过去的三十年中,模糊集理论中的最大-最小组成已在医学诊断中获得了合理的成功,因为它可以估计患者被诊断出患有某种疾病的可能性。但是,尚无理论证明该方法可行的理由。我们创建了一个理论模型来计算假设的患有指定疾病的患者的概率,并使用模拟数据集来解释为什么最大-最小成分成功的原因。另外,基于理论模型,我们提出了一种模糊概率方法来估计患者患某种疾病的可能性。所提出的方法可以产生比最大-最小组成更准确的估计。

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