Hierarchical Latent Class Models and Statistical Foundation for Traditional Chinese Medicine

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Artificial Intelligence in Medicine (AIME 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4594))

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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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Riccardo Bellazzi Ameen Abu-Hanna Jim Hunter

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© 2007 Springer-Verlag Berlin Heidelberg

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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. https://doi.org/10.1007/978-3-540-73599-1_15

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  • DOI: https://doi.org/10.1007/978-3-540-73599-1_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73598-4

  • Online ISBN: 978-3-540-73599-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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