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首页> 外文期刊>Arabian Journal for Science and Engineering >A Fibrosis Diagnosis Clinical Decision Support System Using Fuzzy Knowledge
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A Fibrosis Diagnosis Clinical Decision Support System Using Fuzzy Knowledge

机译：使用模糊知识的纤维化诊断临床决策支持系统

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摘要

Liver cirrhosis, the end stage of chronic liver disease, is one of the major risk factors for the development of liver cancer, and may result in premature death. This research proposes a fuzzy fibrosis decision support (F2DS) system. It is a fuzzy knowledge-based expert system for liver fibrosis stage prediction. F2DS is carefully based on a set of knowledge acquisition and machine learning techniques. In addition, the system depends on domain expert knowledge for designing the membership functions and validating the fuzzy knowledge base. It depends on a suitable list of 17 symptoms, and laboratory test features that can accurately and significantly describe fibrosis patients. The experimental results of the expert system were obtained using a real dataset from the Liver Institute, Mansoura University, Egypt, of 119 patients infected by chronic viral hepatitis C. The performance of the system was evaluated with many metrics, achieving a testing accuracy of 95.7%. The evaluation of proposed fuzzy expert system shows its capability of diagnosing the stages of liver fibrosis with a high degree of accuracy, and it can be embedded as a component in a healthcare system to assist physicians in their daily practice. In addition, students training in medicine can benefit from this system.
机译：肝硬化，慢性肝病的结束阶段，是肝癌发展的主要危险因素之一，可能导致过早死亡。本研究提出了一种模糊纤维化决策支持（F2DS）系统。它是一种模糊知识的专家系统，用于肝纤维化阶段预测。 F2DS根据一套知识获取和机器学习技术仔细。此外，该系统还取决于设计成员函数并验证模糊知识库的域专家知识。这取决于合适的17个症状清单，以及能够准确和显着描述纤维化患者的实验室测试特征。使用慢性病毒乙型肝炎感染的119名患者的肝脏大学肝脏大学肝脏大学肝脏学院的真实数据集获得了专家系统的实验结果。通过许多指标评估了该系统的性能，实现了95.7的测试精度。 ％。拟议的模糊专家系统的评估显示了其具有高精度诊断肝纤维化阶段的能力，并且可以嵌入医疗保健系统中的组件，以帮助医生在日常做法中。此外，医学培训的学生可以从该系统中受益。

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