• DocumentCode
    2506139
  • Title

    Data mining Traditional Chinese Medicine (TCM): Lessons learnt from mining in law and allopathic medicine

  • Author

    Stranieri, Andrew ; Sahama, Tony

  • Author_Institution
    Centre for Inf. & Appl. Optimisation, Univ. of Ballarat, Ballarat, VIC, Australia
  • fYear
    2012
  • fDate
    10-13 Oct. 2012
  • Firstpage
    41
  • Lastpage
    46
  • Abstract
    Key decisions at the collection, pre-processing, transformation, mining and interpretation phase of any knowledge discovery from database (KDD) process depend heavily on assumptions and theoretical perspectives relating to the type of task to be performed and characteristics of data sourced. In this article, we compare and contrast theoretical perspectives and assumptions taken in data mining exercises in the legal domain with those adopted in data mining in TCM and allopathic medicine. The juxtaposition results in insights for the application of KDD for Traditional Chinese Medicine.
  • Keywords
    data mining; learning (artificial intelligence); medical computing; allopathic medicine; data mining; interpretation phase; juxtaposition; knowledge discovery database process; legal domain; traditional chinese medicine; Australia; Cognition; Data mining; Diseases; Law; Medical diagnostic imaging; Data mining; Health informatics; Law; Traditional Chinese Medicine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    e-Health Networking, Applications and Services (Healthcom), 2012 IEEE 14th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4577-2039-0
  • Electronic_ISBN
    978-1-4577-2038-3
  • Type

    conf

  • DOI
    10.1109/HealthCom.2012.6380063
  • Filename
    6380063