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题名: Application of the combination of capillary electrophoresis with wavelet neural network in the assisted clinical diagnosis of breast cancer
作者: Xiong, JH;  Zheng, YF;  Zhang, PD;  Shi, XZ;  Yang, J;  Zhang, YK;  Xu, GW
关键词: wavelet neural network ;  neural network ;  capillary electrophoresis ;  nucleosides ;  urine
刊名: CHEMICAL JOURNAL OF CHINESE UNIVERSITIES-CHINESE
发表日期: 2003-05-01
卷: 24, 期:5, 页:803-807
收录类别: SCI
文章类型: Article
WOS标题词: Science & Technology ;  Physical Sciences
类目[WOS]: Chemistry, Multidisciplinary
研究领域[WOS]: Chemistry
英文摘要: Thirteen kinds of normal and modified nucleosides were determined in urine samples from, 46 healthy persons and 26 breast cancer patients by capillary electrophoresis. A wavelet neural network model has been used as a powerful pattern recognition tool to distinguish breast cancer patients from healthy persons. The recognition rate for the training set reached to 100% and above 96% of people in the predicting set were correctly classified. Compared with standard backpropagation neural network, wavelet neural network had stronger abilities of information extraction and approximation. The results also demonstrated that the predicting ability of wavelet neural network was higher than those of principal component analysis and linear discriminant analysis. The combination of capillary electrophoresis and wavelet neural network was expected to be an assisted tool for the clinical diagnosis of breast cancer.
关键词[WOS]: MODIFIED NUCLEOSIDES ;  SIGNALS
语种: 英语
WOS记录号: WOS:000183017600013
Citation statistics: 
内容类型: 期刊论文
URI标识: http://cas-ir.dicp.ac.cn/handle/321008/138317
Appears in Collections:中国科学院大连化学物理研究所_期刊论文

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作者单位: 1.Chinese Acad Sci, Dalian Inst Chem Phys, Natl Chromatog R & A Ctr, Dalian 116011, Peoples R China

Recommended Citation:
Xiong, JH,Zheng, YF,Zhang, PD,et al. Application of the combination of capillary electrophoresis with wavelet neural network in the assisted clinical diagnosis of breast cancer[J]. CHEMICAL JOURNAL OF CHINESE UNIVERSITIES-CHINESE,2003,24(5):803-807.
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