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Support Vector Machine Approach for Cancer Detection Using Amplified Fragment Length Polymorphism (AFLP) Screening Method

Kong, W., Tan, P., Tham, L. and Wong, K.Y.

    Support Vector Machine is used to classify data obtained from Amplified Fragment length Polymorphism screening of gastric cancer and normal tissue samples. Using the electrophoresis peak intensity measurements of the amplified fragments of the cancer and normal tissues, SVM was able to distinguish gastric cancer from normal tissue samples with a sensitivity of 0.98 and specificity of 0.75. As AFLP is a low cost procedure which requires minimum prior sequence knowledge and biological material, SVM prediction of AFLP screening data is a potential tool for gastric cancer screening and diagnosis.
Cite as: Kong, W., Tan, P., Tham, L. and Wong, K.Y. (2004). Support Vector Machine Approach for Cancer Detection Using Amplified Fragment Length Polymorphism (AFLP) Screening Method. In Proc. Second Asia-Pacific Bioinformatics Conference (APBC2004), Dunedin, New Zealand. CRPIT, 29. Chen, Y.-P. P., Ed. ACS. 63-66.
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