期刊文献+

高斯混合模型对乳腺癌诊断的有效性初探 被引量:1

An Attempt of the Efficiency of GMM in Breast Cancer Diagnosis
下载PDF
导出
摘要 计算机辅助医疗诊断是计算机应用的一个热门方向。本文旨在探讨基于EM算法的高斯混合模型在乳腺癌诊断方面的有效性。通过与现在流行的BP神经网络辅助医疗诊断方法的比较,理论性地说明这种算法的优势,并以实验结果加以证明。 Computer aided medical diagnosis is a heated direction. The paper intended to attempt the efficiency of GMM based on EM algorithm. Compare it with the current popular BP artificial neural network aided medical diagnosis algorithm to comment on its advantages theoretically. At the end of this paper, a proof on factual experiment is given.
作者 曾文蓉
出处 《微计算机信息》 2009年第18期196-198,共3页 Control & Automation
关键词 乳腺癌 EM算法 GMM Breast Cancer EM Algorithm GMM
  • 相关文献

参考文献8

  • 1Xiangchun Xiong, Yangon Kim, Yuncheol Baek, Dae Wong Phee and Soo-Hong Kim. Analysis of breast cancer using data mining & statistical techniques [C]. Proceedings of the Sixth International Conference on SNPD/SAWN'05, Towson, Maryland, 2005: 82--87.
  • 2http://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+ %28Original%29
  • 3Ian H. Witten and Eibe Frank. Data Mining: Practical Machine Learning Tools and Techniques. 2nd Edition [M]. San Francisco: Morgan Kaufmann, 2005.
  • 4Hussein A. Abbass. An Evolutionary Artificial Neural Networks Approach for Breast Cancer Diagnosis [J]. Artificial Intelligence in Medicine, 2002, 25(3): 265--281.
  • 5Arthur P. Dempster, Nan M. Laird and Donald B. Rubint Maximum Likelihood from Incomplete Data via the EM Algorithm [J]. Journal of the Royal Statistical Society. Series B (Methodological), 1977, 39(1): 1-38.
  • 6何仁清,张宏莉.基于EM算法的拥塞链路检测方法[J].微计算机信息,2007,23(02X):121-123. 被引量:2
  • 7David S. Chen and Ramesh C. Jain. A Robust Back Propagation Learning Algorithm for Function Approximation[J]. IEEE transaction on Neural Networks, 1994, 5(3): 467--479.
  • 8http://www.cse.ttu.edu.tw/twyu/www/class/91 -1/Machine% 20 Learning/EM%20Algorit hm.ppt

二级参考文献5

  • 1凌永发,王杰,陈跃斌.网络服务质量性能分析[J].微计算机信息,2006,22(02X):123-125. 被引量:8
  • 2R.Caceres, N.G. Duffield, J.Horowitz et al. Multicast-Based Inference of Network-Internal Characteristics: Accuracy of Packet Loss Estimation [J], IEEE Infocom'99, 1999, 1,371-379
  • 3R.Caceres, N.G. Duffield, J.Horowitz et al. Multicast-Based Inference of Network-Internal Loss Characteristics [J], IEEE Transactions on Information Theory, 1999, 45:2462-2480.
  • 4Coates M, Hero A, Nowak R et al. Intemet Tomography [J], IEEE SIGNAL PROCESSING MAGAZINE, 2002,19(3), 47-66
  • 5Sally Floyd, Van Jacobson. Random Early Detection Gateways for Congestion Avoidance [J], IEEE/ACM Transactions on Networking, 1993, 1(4), 397-413

共引文献1

同被引文献11

引证文献1

二级引证文献14

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部