Hierarchical Latent Class Models and Statistical Foundation for Traditional Chinese Medicine

  • Nevin L. Zhang
  • Shihong Yuan
  • Tao Chen
  • Yi Wang
Conference paper

DOI: 10.1007/978-3-540-73599-1_15

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4594)
Cite this paper as:
Zhang N.L., Yuan S., Chen T., Wang Y. (2007) Hierarchical Latent Class Models and Statistical Foundation for Traditional Chinese Medicine. In: Bellazzi R., Abu-Hanna A., Hunter J. (eds) Artificial Intelligence in Medicine. AIME 2007. Lecture Notes in Computer Science, vol 4594. Springer, Berlin, Heidelberg

Abstract

The theories of traditional Chinese medicine (TCM) originated from experiences doctors had with patients in ancient times. We ask the question whether aspects of TCM theories can be reconstructed through modern day data analysis. We have recently analyzed a TCM data set using a machine learning method and found that the resulting statistical model matches the relevant TCM theory well. This is an exciting discovery because it shows that, contrary to common perception, there are scientific truths in TCM theories. It also suggests the possibility of laying a statistical foundation for TCM through data analysis and thereby turning it into a modern science.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Nevin L. Zhang
    • 1
  • Shihong Yuan
    • 2
  • Tao Chen
    • 1
  • Yi Wang
    • 1
  1. 1.Hong Kong University of Science and Technology, Hong KongChina
  2. 2.Beijing University of Traditional Chinese Medicine, BeijingChina

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