Chinese Journal of Tissue Engineering Research ›› 2010, Vol. 14 ›› Issue (52): 9803-9806.doi: 10.3969/j.issn.1673-8225.2010. 52.028

Previous Articles     Next Articles

Support vector machine for classifying model of nasopharyngeal carcinoma based on microelement

Yang Chun1, Du Xi2, Du Jun2, Tang Bin2, Liu Ke2, Hu Xin3   

  1. 1 Hospital Affiliated to Sinohydro Bureau 10, Dujiangyan  611830, Sichuan Province, China; 2 Department of Chemistry, Luzhou Medical College, Luzhou  646000, Sichuan Province, China; 3 Second Affiliated Hospital of Luzhou Medical College, Luzhou 646000, Sichuan Province, China
  • Online:2010-12-24 Published:2010-12-24
  • Contact: Tang Bin, Master, Associate professor, Department of Chemistry, Luzhou Medical College, Luzhou 646000, Sichuan Province, China tangbin8888@163.com
  • About author:Yang Chun, Attending physician, Hospital Affiliated to Sinohydro Bureau 10, Dujiangyan 611830, Sichuan Province, China
  • Supported by:

    the Key Science and Technology Program of Luzhou, No. 2009-S-15(7/7) *

PDF

408

Abstract:

BACKGROUND: Support vector machine (SVM) has been successfully used in document classification, handwriting recognition, image classification and bioinformatics.
OBJECTIVE: Using intelligent algorithm, to establish model of nasopharyngeal carcinoma (NPC) patients with SVM and microelement data to improve the identification accuracy of NPC.
METHODS: NPC was used to classified model of NPC patients and the normal or the other disease patients based on microelement data. The sample was harvested from non-colored hairs, 3 cm from the scalp. The microelement detection included zinc, copper, ferri, manganese, chromium and nickel, in addition to age and sex. The radical basis function is adopted as a kernel function of SVM, and the model adjusts C and σ to build the optimization classifier.
RESULTS AND CONCLUSION: The correct classification ratio was 81.71% and 66.47% by 10-fold cross validation. The result shows that the classified model of blood routine based on SVM can classifies the nasopharyngeal carcinoma patients from the normal or the other disease patients.

CLC Number: