A Fuzzy Expert System for Diabetes Decision Support Application
A Fuzzy Expert System for Diabetes Decision Support Application
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DOI：
10.1109/tsmcb.2010.2048899
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发表时间：
2011-02-01
影响因子：
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通讯作者：
Wang, Mei-Hui
中科院分区：
文献类型：
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作者：
Lee, Chang-Shing;Wang, Mei-Hui
越来越多的基于领域知识的决策支持系统被用于诊断糖尿病和心脏病等疾病。人们普遍认为，对于某些真实的应用来说，经典本体无法充分处理不精确和模糊的知识，而模糊本体可以有效地解决具有不确定性的数据和知识问题。本文提出了一种新的糖尿病决策支持应用模糊专家系统。在模糊专家系统中建立了一个五层模糊本体，包括模糊知识层、模糊群体关系层、模糊群体领域层、模糊个人关系层和模糊个人领域层，用于描述具有不确定性的知识。通过将新的模糊本体应用于糖尿病领域，定义了模糊糖尿病本体（FDO）的结构，对糖尿病知识进行建模。此外，语义决策支持代理（SDSA），包括知识构建机制，模糊本体生成机制，语义模糊决策机制，也被开发。知识构建机制根据FDO的结构构建模糊概念和模糊关系。FDO的实例由模糊本体生成机制生成。最后，基于FDO和模糊本体，语义模糊决策机制模拟了糖尿病相关应用中医务人员的语义描述。重要的是，建议的模糊专家系统可以有效地为糖尿病决策支持应用。
An increasing number of decision support systems based on domain knowledge are adopted to diagnose medical conditions such as diabetes and heart disease. It is widely pointed that the classical ontologies cannot sufficiently handle imprecise and vague knowledge for some real world applications, but fuzzy ontology can effectively resolve data and knowledge problems with uncertainty. This paper presents a novel fuzzy expert system for diabetes decision support application. A five-layer fuzzy ontology, including a fuzzy knowledge layer, fuzzy group relation layer, fuzzy group domain layer, fuzzy personal relation layer, and fuzzy personal domain layer, is developed in the fuzzy expert system to describe knowledge with uncertainty. By applying the novel fuzzy ontology to the diabetes domain, the structure of the fuzzy diabetes ontology (FDO) is defined to model the diabetes knowledge. Additionally, a semantic decision support agent (SDSA), including a knowledge construction mechanism, fuzzy ontology generating mechanism, and semantic fuzzy decision making mechanism, is also developed. The knowledge construction mechanism constructs the fuzzy concepts and relations based on the structure of the FDO. The instances of the FDO are generated by the fuzzy ontology generating mechanism. Finally, based on the FDO and the fuzzy ontology, the semantic fuzzy decision making mechanism simulates the semantic description of medical staff for diabetes-related application. Importantly, the proposed fuzzy expert system can work effectively for diabetes decision support application.