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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：基于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：肝硬化是慢性肝病的终末期，是发展肝癌的主要危险因素之一，并可能导致过早死亡。这项研究提出了一个模糊的纤维化决策支持（F2DS）系统。它是用于肝纤维化阶段预测的基于模糊知识的专家系统。 F2DS仔细地基于一组知识获取和机器学习技术。另外，该系统依赖于领域专家知识来设计隶属度函数并验证模糊知识库。它取决于17种症状的适当列表以及可以准确，显着描述纤维化患者的实验室测试功能。使用来自埃及曼苏拉大学肝病研究所的真实数据集，对119例慢性丙型肝炎病毒感染患者进行了专家系统的实验结果。该系统的性能得到了许多指标的评估，测试准确性达到95.7 ％。对所提出的模糊专家系统的评估显示出其能够高度准确地诊断肝纤维化阶段的能力，并且可以作为医疗系统的组成部分来嵌入，以帮助医师进行日常实践。此外，医学培训的学生可以从该系统中受益。

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