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Hierarchical Latent Class Models and Statistical Foundation for Traditional Chinese Medicine

  • Nevin L. Zhang
  • Shihong Yuan
  • Tao Chen
  • Yi Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4594)

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.

Keywords

Latent Variable Traditional Chinese Medicine Manifest Variable Symptom Variable Traditional Chinese Medicine Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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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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