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Network differentiation: A computational method of pathogenesis diagnosis in traditional Chinese medicine based on systems science

机译:网络分化:基于系统科学的中医药病发发生诊断的计算方法

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摘要

Resembling the role of disease diagnosis in Western medicine, pathogenesis (also called Bing Ji) diagnosis is one of the utmost important tasks in traditional Chinese medicine (TCM). In TCM theory, pathogenesis is a complex system composed of a group of interrelated factors, which is highly consistent with the character of systems science (SS). In this paper, we introduce a heuristic definition called pathogenesis network (PN) to represent pathogenesis in the form of the directed graph. Accordingly, a computational method of pathogenesis diagnosis, called network differentiation (ND), is proposed by integrating the holism principle in SS. ND consists of three stages. The first stage is to generate all possible diagnoses by Cartesian Product operated on specified prior knowledge corresponding to the input symptoms. The second stage is to screen the validated diagnoses by holism principle. The third stage is to pick out the clinical diagnosis by physician-computer interaction. Some theorems are stated and proved for the further optimization of ND in this paper. We conducted simulation experiments on 100 clinical cases. The experimental results show that our proposed method has an excellent capability to fit the holistic thinking in the process of physician inference.
机译:类似于疾病诊断在西医中的作用,发病机制(也称为Bing Ji)诊断是中药(TCM)最重要的任务之一。在TCM理论中,发病机制是由一组相互关联因子组成的复杂系统,这与系统科学的特征高度一致(SS)。在本文中,我们介绍了一种称为致病机网络(PN)的启发式定义,以表示指向图形式的发病机制。因此,通过在SS中整合全球原理,提出了一种称为网络分化(ND)的发病机制诊断的计算方法。 ND由三个阶段组成。第一阶段是通过对应于输入症状对应的指定先前知识操作的笛卡尔产品的所有可能诊断。第二阶段是通过全美原理筛选验证的诊断。第三阶段是通过医师 - 计算机互动挑选临床诊断。在本文中陈述了一些定理,并证明了ND的进一步优化。我们对100次临床病例进行了仿真实验。实验结果表明,我们所提出的方法具有良好的能力,可以在医生推理过程中适应整体思维。

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