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Raman spectral statistical classification of nasopharyngeal carcinoma and nasopharyngeal normal cell lines based on support vector classification

机译:基于支持向量分类的鼻咽癌和鼻咽正常细胞株的拉曼光谱统计分类

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摘要

Raman spectroscopy (RS) has been used in the discrimination of normal and tumor cells for years. It is very important to validate an existing classification model using different algorithms. In this work, two algorithms of support vector classification (SVC) are utilized to validate our previous work about a LDA classification model of nasopharyngeal carcinoma (NPC) cell lines C666-1, CNE2 and nasopharyngeal normal cell line NP69. All of these two SVC algorithms use the same data set as the previous LDA model and, achieve great sensitivity and specificity. The final results show that our previous LDA classification model could be supported by different SVC algorithms and this demonstrates our classification model is reliable and may be helpful to the realization of RS to be one of diagnostic techniques of NPC.
机译:拉曼光谱法(RS)已用于判别正常细胞和肿瘤细胞多年。使用不同的算法来验证现有分类模型非常重要。在这项工作中,使用两种支持向量分类算法(SVC)来验证我们先前关于鼻咽癌(NPC)细胞系C666-1,CNE2和鼻咽正常细胞系NP69的LDA分类模型的工作。所有这两种SVC算法都使用与以前的LDA模型相同的数据集,并且具有很高的灵敏度和特异性。最终结果表明,我们以前的LDA分类模型可以被不同的SVC算法支持,这表明我们的分类模型是可靠的,并且可能有助于RS成为NPC的诊断技术之一。

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