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TCM Data Mining and Quality Evaluation with SAPHRONTM System

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Data Analytics for Traditional Chinese Medicine Research

Abstract

Traditional Chinese Medicine (TCM) is an invaluable human heritage for its documented clinical experience of thousands of years. However, it remains problematic for how to make the best use of this treasure. A major concern of TCM modernization is the credibility of the information. A large number of these clinical records are scattered in various notes, books and research reports and there is absence of good tool to scientifically evaluate this tremendous amount of information. Our recent preliminary study has shown that the quality of TCM information is generally poor and unreliable. To provide a platform that provides TCM information with verified quality as a base for TCM-originated product development, we established a proprietary SAPHRON TCM data system to quantitatively evaluate the quality of TCM information, which ranks TCM prescriptions, herbs, active ingredients as well as potential lead compounds based on the reliability of available information for recommendation. Our results have showed that, scientific approaches with modern technology of informatics and statistics can be applied to TCM information in a high throughput fashion.

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Author information

Authors and Affiliations

  1. Shanghai Innovative Research Centre of Traditional Chinese Medicine, Shanghai, China

    Jing Yang, Hua Su, Guoshun Tang, Zihan Zheng, Yue Shen, Lei Zhang, Hongyan Wei, Songxia Yin, Lu Chen, Zirong Yang & William Jia

  2. Brain Research Centre and Department of Surgery, University of British Columbia, Vancouver, BC, Canada

    William Jia

Authors
  1. Jing Yang
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  2. Hua Su
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  3. Guoshun Tang
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  4. Zihan Zheng
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  5. Yue Shen
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  6. Lei Zhang
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  7. Hongyan Wei
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  8. Songxia Yin
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  9. Lu Chen
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  10. Zirong Yang
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  11. William Jia
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Corresponding author

Correspondence to William Jia .

Editor information

Editors and Affiliations

  1. University of Sydney, Sydney, New South Wales, Australia

    Josiah Poon

  2. University of Sydney, Sydney, New South Wales, Australia

    Simon K. Poon

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© 2014 Springer International Publishing Switzerland

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Yang, J. et al. (2014). TCM Data Mining and Quality Evaluation with SAPHRONTM System. In: Poon, J., K. Poon, S. (eds) Data Analytics for Traditional Chinese Medicine Research. Springer, Cham. https://doi.org/10.1007/978-3-319-03801-8_12

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  • DOI: https://doi.org/10.1007/978-3-319-03801-8_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03800-1

  • Online ISBN: 978-3-319-03801-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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