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Bridging Fatty Liver Disease and Traditional Chinese Medicine: A Complex Network Approach

机译：脂肪肝与中医药的桥梁：复杂的网络方法

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The integration of traditional Chinese medicine (TCM) and modern medicine (MM) focuses on the wellness and healing of the whole person, and promises an improved treatment. Yet it is not well known what the correlation between TCM symptoms and MM symptoms is, and how such correlation changes in a certain disease. In this paper, we construct the symptom networks and compare the topology of the networks between the fatty liver disease (FLD) patients group and the healthy controls group, with the physical and TCM examination data. Specifically, we explore the correlation between TCM and MM symptoms. Furthermore, the centrality metrics such as eigenvector centrality, h-degree and c-index, are used to identify the significant symptoms. Moreover, to validate the effectiveness of the identification of significant symptoms, we quantify the ability of these symptoms as biomarkers to distinguish FLD patients and healthy controls. Our results demonstrate that the construction of symptom networks and centrality metrics shed a new light on the analysis of the correlation among symptoms and the recognition of significant symptoms.
机译：中医（TCM）和现代医学（MM）的融合着眼于整个人的健康和康复，并有望改善治疗方法。然而，还不知道中医症状和MM症状之间的相关性是什么，以及这种相关性在某种疾病中是如何变化的。在本文中，我们构建了症状网络，并通过物理和中医检查数据比较了脂肪肝疾病（FLD）患者组和健康对照组之间的网络拓扑。具体来说，我们探讨了中医与MM症状之间的相关性。此外，诸如特征向量中心度，h-度和c-指数之类的中心度度量用于识别明显症状。此外，为了验证识别重大症状的有效性，我们将这些症状作为生物标记物区分FLD患者和健康对照者的能力进行了量化。我们的结果表明，症状网络和集中度指标的构建为症状之间的相关性分析和重要症状的识别提供了新的思路。

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