Data mining traditional Chinese medicine (TCM) lessons learnt from mining in law and allopathic medicine
Stranieri, Andrew & Sahama, Tony R. (2012) Data mining traditional Chinese medicine (TCM) lessons learnt from mining in law and allopathic medicine. In Song, Jian (Ed.) Proceedings of the 2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom), IEEE, Beijing, China.
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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 theorectical 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.
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|Item Type:||Conference Paper|
|Keywords:||Component, Data mining, Traditional Chinese Medicine, Law, Health informatics|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > OTHER INFORMATION AND COMPUTING SCIENCES (089900)|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Deposited On:||23 Oct 2012 01:35|
|Last Modified:||19 Feb 2013 04:20|
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