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Journal of Biomedical Engineering ; (6): 1045-1048, 2005.
Article in Chinese | WPRIM | ID: wpr-238282

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.


Subject(s)
Humans , Algorithms , Artificial Intelligence , Data Interpretation, Statistical , Early Diagnosis , Models, Statistical , Neoplasms , Diagnosis , Neural Networks, Computer , Pattern Recognition, Automated
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