Hepatitis B is a widespread epidemic in the world, but so far no single drug has been shown to kill or eliminate the Hepatitis B virus and heal people with chronic Hepatitis B virus infection. Based on comprehensive investigations to relevant characteristics of Hepatitis B, a diagnostic modelling and reasoning methodology using Dynamic Uncertain Causality Graph is proposed. The symptoms, physical signs, examinations results, medical histories, etiology, pathogenesis and other factors were included in the diagnosis model. In order to reduce the difficulty of building the model, a modular modeling scheme is proposed, which provides multi-perspectives and arbitrary granularity for the expression of disease causality. The chain reasoning algorithm and weighted logic operation mechanism are introduced to ensure the correctness and effectiveness of diagnostic reasoning under incomplete and uncertain information. In addition, the causal view of the potential interactions between diseases and symptoms visually shows the reasoning process in a graphical way. In the relevant model, the model of the diagnostic process and the model of the therapeutic process are symmetrical. The results show that, even with incomplete observations, the proposed methodology achieves encouraging diagnostic accuracy and effectiveness, providing a promising assistance tool for physicians in the diagnosis of Hepatitis B.

中文翻译：

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面向乙肝智能诊断和治疗的动态不确定因果关系图

乙型肝炎在世界范围内广泛流行，但迄今为止，还没有一种药物被证明可以杀死或消除乙型肝炎病毒并治愈慢性乙型肝炎病毒感染者。基于对乙型肝炎相关特征的综合调查，提出了一种基于动态不确定因果关系图的诊断建模和推理方法。将症状、体征、检查结果、病史、病因、发病机制等因素纳入诊断模型。为了降低模型构建的难度，提出了模块化建模方案，为疾病因果关系的表达提供了多视角和任意粒度。引入链式推理算法和加权逻辑运算机制，保证在不完全和不确定信息下诊断推理的正确性和有效性。此外，疾病和症状之间潜在相互作用的因果视图以图形方式直观地显示了推理过程。在相关模型中，诊断过程模型和治疗过程模型是对称的。结果表明，即使观察不完整，所提出的方法也实现了令人鼓舞的诊断准确性和有效性，为医生诊断乙型肝炎提供了有希望的辅助工具。疾病和症状之间潜在相互作用的因果视图以图形方式直观地显示了推理过程。在相关模型中，诊断过程模型和治疗过程模型是对称的。结果表明，即使观察不完整，所提出的方法也实现了令人鼓舞的诊断准确性和有效性，为医生诊断乙型肝炎提供了有希望的辅助工具。疾病和症状之间潜在相互作用的因果视图以图形方式直观地显示了推理过程。在相关模型中，诊断过程模型和治疗过程模型是对称的。结果表明，即使观察不完整，所提出的方法也实现了令人鼓舞的诊断准确性和有效性，为医生诊断乙型肝炎提供了有希望的辅助工具。