Analysis of cardiac imaging data using decision tree based parallel genetic programming
Analysis of cardiac imaging data using decision tree based parallel genetic programming
复制标题
使用基于决策树的并行遗传编程分析心脏成像数据
DOI：
10.1109/ispa.2009.5297730
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
T. Pham
中科院分区：
文献类型：
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作者：
Cuong To;T. Pham
我们提出了一种生成心脏诊断规则的算法。诊断规则以决策树的形式呈现，这些决策树由遗传编程创建。利用心脏单质子发射计算机断层扫描图像对该算法进行了验证。与支持向量机、LogitBoost、Logistic回归、线性判别分析、线性回归和最小二乘等六种常用方法相比，该算法具有较好的性能。我们还证明了并行遗传编程可以用来提高所提算法的性能。
We propose an algorithm for generating diagnostic rules for cardiac diagnoses. Diagnostic rules are presented in decision tree forms that are created by genetic programming. The algorithm was tested by using cardiac single proton emission computed tomography images. In comparisons with other six well-known methods including support vector machine, LogitBoost, logistic regression, linear discriminant analysis, linear regression and least square methods; the proposed algorithm is superior. We also show that parallel genetic programming can be used to improve the performance of the proposed algorithm.
DOI：
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发表时间：
1992
期刊：
--
影响因子：
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作者：
J. Koza
通讯作者：
J. Koza