Raman spectral statistical classification of nasopharyngeal carcinoma and nasopharyngeal normal cell lines based on support vector classification. Issue 4 (2011) - Chen Chen, Yang Yang; Sun Sun, Lei Lei; Huang Huang, Yangwen Yangwen; Ou Ou, Lin Lin; Su Su, Ying Ying
Abstract : 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.