| 基于粗糙集和BP神经网络的心脏病病症诊断方法 |
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| 引用本文： | 史爱松,张秉森.基于粗糙集和BP神经网络的心脏病病症诊断方法[J].青岛大学学报(自然科学版),2005,18(3):59-62. |
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| 作者姓名： | 史爱松 张秉森 |
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| 作者单位： | 青岛大学信息工程学院,山东,青岛,266071;青岛大学信息工程学院,山东,青岛,266071 |
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| 摘 要： | 提出了把粗糙集和BP神经网络结合应用于心脏病病症诊断的方法,用经Konhonen网络量化后的心脏病病人病症数据及诊断结果建立决策表,使用粗糙集理论进行属性约简,约简后的病症数据作为BP神经网络的输入,诊断结果作为BP神经网络的输出.通过实际病例的诊断表明,利用粗糙集和BP神经网络相结合的方法,可有效提高心脏病症诊断的精度和速度,同时也减少了检查项目,降低了诊断成本.
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| 关 键 词： | 心脏病 粗糙集 神经网络 计算机辅助诊断 |
| 文章编号： | 1006-1037（2005）03-0059-04 |
| 收稿时间： | 2005-02-05 |
| 修稿时间： | 2005年2月5日 |
Method of Cardiopathy Diagnosis Based on Rough Sets Theory and Neural Network |
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| SHI Ai-song,ZHANG Bing-sen.Method of Cardiopathy Diagnosis Based on Rough Sets Theory and Neural Network[J].Journal of Qingdao University(Natural Science Edition),2005,18(3):59-62. |
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| Authors: | SHI Ai-song ZHANG Bing-sen |
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| Institution: | College of Information Engineering, Qingdao University, Qingdao 266071, China |
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| Abstract: | Based on rough sets a neural network model theory for cardiopathy symptoms diagnosis is proposed. According to the cardiopathy symptoms data quantized by Konhonen neural network, a decision table is structured and is reduced using the rough sets theory. After reducing the decision table, the symptoms data are of the input the BP neural network's input, and the diagnosis data are the output. The practical application shows that using a BP neural network with rough sets theory can enhance effectively accuracy and speed of diagnosis and reduce some checking items and checking cost. |
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| Keywords: | cardiopathy ro ugh sets neural network CAD |
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