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Comparative Study of Classifiers for Prediction of Recurrence of Liver Cancer Using Binary Patterns

  • Hiroyuki Ogihara
  • Yusuke Fujita
  • Norio Iizuka
  • Masaaki Oka
  • Yoshihiko Hamamoto
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8482)

Abstract

Liver cancer has a high likelihood of recurrence despite complete surgical resection and is thus known as an intractable cancer. If postoperative recurrence of cancer is correctly predicted for each patient as a form of personalized medicine, effective treatment can be carried out. The purpose of this paper is to evaluate classifiers for predicting recurrence of liver cancer by use of blood test data only in patients who underwent complete surgical resection of liver cancer. We conduct comparative study of 3 classifiers with use of binary patterns, which consist of clinical data and genomic data.

Keywords

Cancer Diagnosis Classifier Binary Pattern Boolean Algebra 

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References

  1. 1.
    Iizuka, N., Oka, M., Hamamoto, Y., et al.: Oligonucleotide microarray for prediction of early intrahepatic recurrence of hepatocellular carcinoma after curative resection. Lancet, 923–929 (2003)Google Scholar
  2. 2.
    Youden, W.J.: Index for rating diagnostic tests. Cancer 3, 32–35 (1950)CrossRefGoogle Scholar
  3. 3.
    Jain, A.K., Duin, R.W., Mao, J.: Statistical pattern recognition: A review. IEEE Trans. Pattern Anal. Mach. Intell. 22, 4–37 (2000)CrossRefGoogle Scholar
  4. 4.
    Guttman, I., Wilks, S.S.: Introductory Engineering Statistics. John Wiley & Sons (1965)Google Scholar
  5. 5.
    Moribe, T., et al.: Methylation of multiple genes as molecular markers for diagnosis of a small well-differentiated hepatocellular carcinoma. Int. J. Cancer 125, 388–397 (2009)CrossRefGoogle Scholar
  6. 6.
    Duda, R.O., Hart, P.E.: Pattern Classification and Scene Analysis. John Wiley & Sons (1973)Google Scholar
  7. 7.
    Chow, C.K.: A recognition method using neighbor dependence. IRE Trans., Elec. Comp. EC-11, 683–690 (1962)Google Scholar
  8. 8.
    Ogihara, H., Fujita, Y., Iizuka, N., Oka, M., Hamamoto, Y.: Classification Based on Boolean Algebra and its Application to the Prediction of Recurrence of Liver Cancer. In: Proc. of Workshop on Recent Advances in Computer Vision and Pattern Recognition, pp. 838–841 (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Hiroyuki Ogihara
    • 1
  • Yusuke Fujita
    • 1
  • Norio Iizuka
    • 2
  • Masaaki Oka
    • 2
  • Yoshihiko Hamamoto
    • 1
  1. 1.Graduate School of MedicineYamaguchi UniversityUbeJapan
  2. 2.Graduate School of MedicineYamaguchi UniversityUbeJapan

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