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The Scientific World Journal
Volume 2015 (2015), Article ID 859192, 9 pages
http://dx.doi.org/10.1155/2015/859192
Research Article

Pulse Diagnosis Signals Analysis of Fatty Liver Disease and Cirrhosis Patients by Using Machine Learning

1Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing 100700, China
2Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
3GULOU Hospital of TCM of Beijing, Beijing 100009, China
4Tai Yang Gong Health Care Center, Chaoyang District, Beijing 100102, China
5Shi Xuemin Academician Office, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China

Received 21 January 2015; Revised 28 May 2015; Accepted 15 November 2015

Academic Editor: Zhaohui Liang

Copyright © 2015 Wang Nanyue et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. G.-Z. Li, S. Sun, M. You, Y.-L. Wang, and G.-P. Liu, “Inquiry diagnosis of coronary heart disease in Chinese medicine based on symptom-syndrome interactions,” Chinese Medicine, vol. 7, article 9, 2012. View at Publisher · View at Google Scholar · View at Scopus
  2. H. Shao, G.-Z. Li, G. Liu, and Y. Wang, “Symptom selection for multi-label data of inquiry diagnosis in traditional Chinese medicine,” Science China Information Sciences, vol. 56, no. 5, Article ID 052118, pp. 1–13, 2013. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  3. F. Li, C. Zhao, Z. Xia, Y. Wang, X. Zhou, and G.-Z. Li, “Computer-assisted lip diagnosis on traditional Chinese medicine using multi-class support vector machines,” BMC Complementary and Alternative Medicine, vol. 12, article 127, 2012. View at Publisher · View at Google Scholar · View at Scopus
  4. N.-Y. Wang, Y.-H. Yu, D.-W. Huang et al., “Research of features in the pulse waves of women during pregnancy,” in Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW '10), pp. 730–732, IEEE, Hong Kong, December 2010. View at Publisher · View at Google Scholar
  5. N.-Y. Wang, Y.-H. Yu, D.-W. Huang et al., “Research of pulse wave's change of rats after kidney resection,” China Journal of Traditional Chinese Medicine and Pharmacy, vol. 24, no. 6, pp. 796–798, 2009. View at Google Scholar
  6. N.-Y. Wang, Y.-H. Yu, D.-W. Huang et al., “Research of pulse wave's features about rats of CHF model,” China Journal of Traditional Chinese Medicine and Pharmacy, vol. 12, pp. 1953–1955, 2010. View at Google Scholar
  7. L.-Y. Xue, N.-Y. Wang, Y.-H. Yu et al., “Research of features in the pulse waves of HBP patients based on principal component analysis and LS,Lasso,” Chinese Journal of Basic Medicine in Traditional Chinese Medicine, vol. 6, pp. 660–663, 2013. View at Google Scholar
  8. K. Omagari, Y. Kadokawa, J.-I. Masuda et al., “Fatty liver in non-alcoholic non-overweight Japanese adults: incidence and clinical characteristics,” Journal of Gastroenterology and Hepatology, vol. 17, no. 10, pp. 1098–1105, 2002. View at Publisher · View at Google Scholar · View at Scopus
  9. M. Hilden, P. Christoffersen, E. Juhl, and J. B. Dalgaard, “Liver histology in a ‘normal’ population—examinations of 503 consecutive fatal traffic casualties,” Scandinavian Journal of Gastroenterology, vol. 12, no. 5, pp. 593–597, 1977. View at Publisher · View at Google Scholar · View at Scopus
  10. L. Shen, J.-G. Fan, Y. Shao et al., “Prevalence of nonalcoholic fatty liver among administrative officers in Shanghai: an epidemiological survey,” World Journal of Gastroenterology, vol. 9, no. 5, pp. 1106–1110, 2003. View at Google Scholar · View at Scopus
  11. B.-L. Lou, E.-L. Xue, N. Fu et al., “Incidence of non-alcoholic fatty liver diseaseandits risk factors in navy flight crew and the submariners,” Journal of Preventive Medicine of Chinese People's Liberation Army, vol. 1, pp. 20–22, 2013. View at Google Scholar
  12. W. A. Zatoński, U. Sulkowska, M. Mańczuk et al., “Liver cirrhosis mortality in Europe, with special attention to Central and Eastern Europe,” European Addiction Research, vol. 16, no. 4, pp. 193–201, 2010. View at Publisher · View at Google Scholar · View at Scopus
  13. Z.-F. Fei, Chinese Pulse Diagnosis Research, Shanghai Publishing Company of Traditional Chinese Medicine, 1991.
  14. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, World Publishing Company, New York, NY, USA, 2009.
  15. G.-Z. Li, H.-L. Bu, M. Q. Yang, X.-Q. Zeng, and J. Y. Yang, “Selecting subsets of newly extracted features from PCA and PLS in microarray data analysis,” BMC Genomics, vol. 9, supplement 2, article S24, 2008. View at Publisher · View at Google Scholar · View at Scopus
  16. G. Jianchao, Application of Lasso and related methods in generalized linear models selection [M.S. thesis], Central South University, Changsha, China, 2001.
  17. R. Tibshirani, “Regression shrinkage and selection via the lasso,” Journal of the Royal Statistical Society Series B: Methodological, vol. 58, no. 1, pp. 267–288, 1996. View at Google Scholar · View at MathSciNet
  18. I. E. Frank and J. H. Friedman, “A statistical view of some chemometrics regression tools,” Technometrics, vol. 35, no. 2, pp. 109–135, 1993. View at Publisher · View at Google Scholar
  19. L. Breiman, “Better subset regression using the nonnegative garrote,” Technometrics, vol. 37, no. 4, pp. 373–384, 1995. View at Publisher · View at Google Scholar · View at MathSciNet