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面向乳腺癌辅助诊断的改进支持向量机方法
Alternative TitleImproved method for computer-aided diagnosis of breast cancer based on support vector machines
章永来; 史海波; 尚文利; 周晓锋; 纪晓楠
Department数字工厂研究室
Source Publication计算机应用研究
ISSN1001-3695
2013
Volume30Issue:8Pages:2373-2376
Indexed ByCSCD
CSCD IDCSCD:4909655
Contribution Rank1
Funding Organization国家自然科学基金项目(61164012)
Keyword机器学习 支持向量机 乳腺癌 辅助诊断 分类
Abstract

目前在全世界范围内,乳腺癌已经成为妇女病死的重要原因之一。文章根据针吸细胞学方法影像中提取的特征值,设计了一种改进的支持向量机分类方法,并应用于该疾病的辅助诊断。通过几种常用核函数的对比分析,所建立的新核函数在诊断中具有很好的综合性能。使用实际临床数据分析显示,该方法比模因佩雷托(Memetic Pareto Artificial Neural Network, MPANN)与一种改进型人工神经网络(Evolutionary Artificial Neural Network, EANN)方法在乳腺癌辅助诊断中具有更好的效果, 可以为医疗机构对该疾病的诊断提供有力的决策支持。

Other Abstract

According to features from a digitized image of a fine needle aspirate, this paper proposed an evolutionary classification method based on support vector machines for the disease diagnosis. Through the contrastive analysis using some common kernel functions, it showed experimentally that the new created kernel function has better integrative capability than original kernel functions. Compared with MPANN and EANN approach, this method has more effective in computer-aided diagnosis of breast cancer using the same clinical data,which can support the medical domain efficiently.

Language中文
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/12481
Collection数字工厂研究室
Affiliation1.中国科学院沈阳自动化研究所
2.中国科学院大学
3.辽宁工程技术大学
Recommended Citation
GB/T 7714
章永来,史海波,尚文利,等. 面向乳腺癌辅助诊断的改进支持向量机方法[J]. 计算机应用研究,2013,30(8):2373-2376.
APA 章永来,史海波,尚文利,周晓锋,&纪晓楠.(2013).面向乳腺癌辅助诊断的改进支持向量机方法.计算机应用研究,30(8),2373-2376.
MLA 章永来,et al."面向乳腺癌辅助诊断的改进支持向量机方法".计算机应用研究 30.8(2013):2373-2376.
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