Application of support vector machine in the detection of early cancer.
- Author:
Zhiyong GAO
1
;
Jianya GONG
;
Qianqing QIN
;
Jiarui LIN
Author Information
1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China. zhiyong-gao@163.com
- Publication Type:Journal Article
- MeSH:
Algorithms;
Artificial Intelligence;
Data Interpretation, Statistical;
Early Diagnosis;
Humans;
Models, Statistical;
Neoplasms;
diagnosis;
Neural Networks (Computer);
Pattern Recognition, Automated
- From:
Journal of Biomedical Engineering
2005;22(5):1045-1048
- CountryChina
- Language:Chinese
-
Abstract:
Support Vector Machine (SVM) is an efficient novel method originated from the statistical learning theory. It is powerful in machine learning to solve problems with finite samples. Due to the deficiency of cancer cells, character of patient and noise in the raw data, it is very difficult to diagnose early cancer accurately. In this paper, SVM is employed in detecting early cancer and the results are encouraged compared with conventional methods. The accuracy of Non-linear SVM classifier is especially high in all kinds of classifiers, which indicates the potential application of SVM in early cancer detection.
