| 数据挖掘在医疗数据中的应用 |
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| 引用本文： | 叶明全. 数据挖掘在医疗数据中的应用[J]. 安徽工程科技学院学报：自然科学版, 2007, 22(3): 54-57 |
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| 作者姓名： | 叶明全 |
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| 作者单位： | 皖南医学院,计算机教研室,安徽,芜湖,241000 |
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| 基金项目： | 安徽省教育厅自然科学基金资助项目(2005kj094) |
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| 摘 要： | 决策树是医疗数据挖掘中一种重要分类方法,针对原始医疗数据存在大量重复样本和冗余属性,影响医疗诊断的精度和速度这一问题,提出了一种基于粗糙集和ID3算法相结合的决策树方法.将所提方法应用于冠心病诊断决策,并对属性约简前后的决策性能进行了比较分析.实验表明了该方法的有效性和实用性.
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| 关 键 词： | 数据挖掘 粗糙集 决策树 ID3算法 医疗数据 |
| 文章编号： | 1672-2477（2007）03-0054-04 |
| 修稿时间： | 2007-01-23 |
Application of data mining in medical diagnosis data |
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| YE Ming-quan. Application of data mining in medical diagnosis data[J]. Journal of Anhui University of Technology and Science, 2007, 22(3): 54-57 |
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| Authors: | YE Ming-quan |
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| Affiliation: | Comp. Staff. Room. , WanNan Medical College, Wuhu 241000, China |
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| Abstract: | It was found that the precision and speed of medical diagnosis is unsatisfactory due to large-scale repeating data and redundant attributes in medical data in practice.To solve the problem,a new model based on rough set and decision tree ID3 is presented.The theory of rough set reduces the initial sample sets,while the decision tree ID3 is used to learn quickly the reduced decision tables and form a tree classifier.An example is given to show the validity and practicability of the new mode1. |
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| Keywords: | data mining rough set decision tree ID3 algorithm medical diagnosis data |
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