• DocumentCode
    2380012
  • Title

    Studying herb-herb interaction for insomnia through the theory of complementarities

  • Author

    Poon, Josiah ; Poon, Simon ; Yin, Dawei ; Chan, Kelvin ; Loy, Clement ; Zhou, Xuezhong ; Zhang, Runshun ; Liu, Baoyan ; Kwan, Paul ; Sze, Daniel ; Gao, Junbin

  • Author_Institution
    Univ. of Sydney, Sydney, NSW, Australia
  • fYear
    2010
  • fDate
    18-18 Dec. 2010
  • Firstpage
    722
  • Lastpage
    726
  • Abstract
    The efficacy of a TCM medication derives from the herb-herb interaction in a formula. Although there are standard formulae, a practitioner will only pick a subset of formulas as templates and personalize them for the patients. It is not easy to determine the true interacting herbs to contribute to the effectiveness of a treatment. Association rule mining is an approach to find the co-occurrence of some items, however, it is not goal-oriented, and the generated results are very sensitive to the given parameters, i.e. support count. The aim of this paper is to introduce a new framework to systematically generate a set of combinations of interacting herbs that leads to good outcome. This algorithm was tested with a dataset of treatment of insomnia to understand the effectiveness of combination of herbs. Interesting and insightful results were noted and discussed.
  • Keywords
    data mining; medical computing; medical disorders; patient treatment; pharmaceuticals; TCM medication; association rule mining; complementarities theory; herb-herb interaction; insomnia treatment; traditional Chinese medicine; complementarity; insomnia; interaction; super-modular function;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine Workshops (BIBMW), 2010 IEEE International Conference on
  • Conference_Location
    Hong, Kong
  • Print_ISBN
    978-1-4244-8303-7
  • Electronic_ISBN
    978-1-4244-8304-4
  • Type

    conf

  • DOI
    10.1109/BIBMW.2010.5703897
  • Filename
    5703897