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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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 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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ID Code: 54262
Item Type: Conference Paper
Refereed: Yes
Keywords: Component, Data mining, Traditional Chinese Medicine, Law, Health informatics
ISBN: 9781457720383
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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