Fast algorithm of support vector machines in lung cancer diagnosis

被引：4
|
作者：
Liu, WQ [1 ]
Shen, PH [1 ]
Qu, YY [1 ]
Xia, DH [1 ]
机构：
[1] Nanjing Univ Sci & Tech, Dept Comp, Comp Vis Lab, Nanjing 210094, Peoples R China
来源：
INTERNATIONAL WORKSHOP ON MEDICAL IMAGING AND AUGMENTED REALITY, PROCEEDINGS | 2001年
关键词：
support vector machines; sequential minimal optimization; game theory; lung cancer diagnosis;
D O I：
10.1109/MIAR.2001.930284
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
In this paper, a method of lung cancer aid diagnosis using Support Vector Machines is proposed. Combined with the knowledge of pathology, the improvement of Sequential Minimal Optimization (SMO) is achieved by the introduction of Game Theory to accelerate the training process. The experiments result shows that the speed increased greatly. And comparing with other systems, the diagnosis identification rate of the three main kinds of cancer cells is also increased.
引用
收藏
页码：188 / 192
页数：5
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