Support Vector Machine approach for cancer detection using Amplified Fragment length Polymorphism (AFLP) screening method

机译：支持向量机方法使用扩增片段长度多态性（AFLP）筛选方法进行癌症检测

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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 senssitivity 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.

机译：支持向量机用于对从胃癌和正常组织样本的扩增片段长度多态性筛选中获得的数据进行分类。通过对癌症和正常组织的扩增片段的电泳峰强度测量，SVM能够以0.98的灵敏度和0.75的特异性将胃癌与正常组织样品区分开。由于AFLP是一种低成本程序，需要最少的先验序列知识和生物学材料，因此AFLP筛查数据的SVM预测是胃癌筛查和诊断的潜在工具。

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来源
《Proceedings of the Second conference on Asia-Pacific bioinformatics》|2004年|P.63-66|共4页
会议地点 Dunedin(NZ)
作者
Waiming Kong; Lawrence Tham; Kee Yew Wong; Patrick Tan;
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作者单位

Nanyang Polytechnic, Singapore;

National Cancer Centre of Singapore, Singapore;

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会议组织
原文格式 PDF
正文语种 eng
中图分类生物工程学（生物技术）;
关键词
cancer detection;

机译：癌症检测;

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Support Vector Machine approach for cancer detection using Amplified Fragment length Polymorphism (AFLP) screening method

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