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Context-Awareness Healthcare for Disease Reasoning Based on Fuzzy Logic
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 Title & Authors
Context-Awareness Healthcare for Disease Reasoning Based on Fuzzy Logic
Lee, Byung-Kwan; Jeong, Eun-Hee; Lee, Sang-Sik;
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This paper proposes Context-Awareness Healthcare for Disease Reasoning based on Fuzzy Logic. It consists of a Fuzzy-based Context-Awareness Module (FCAM) and a Fuzzy-based Disease Reasoning Module (FDRM). The FCAM computes a Correlation coefficient and Support between a Condition attribute and a Decision attribute and generates Fuzzy rules by using just the Condition attribute whose Correlation coefficient and Support are high. According to the result of accuracy experiment using a SIPINA mining tool, those generated by Fuzzy Rule based on Correlation coefficient and Support (FRCS) and Improved C4.5 are 0.84 and 0.81 each average. That is, compared to the Improved C4.5, the FRCS reduces the number of generated rules, and improves the accuracy of rules. In addition, the FDRM can not only reason a patient’s disease accurately by using the generated Fuzzy Rules and the patient disease information but also prevent a patient’s disease beforehand.
Fuzzy-based context-awareness module(FCAM);Fuzzy-based disease reasoning module (FDRM);Fuzzy set;Fuzzy rules;Context-awareness information;Correlation coefficient;Support;
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