- Title
- Data mining Traditional Chinese Medicine (TCM) : Lessons learnt from mining in law and allopathic medicine
- Creator
- Stranieri, Andrew; Sahama, Tony
- Date
- 2012
- Type
- Text; Conference proceedings
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/63336
- Identifier
- vital:4875
- Identifier
-
https://doi.org/10.1109/HealthCom.2012.6380063
- 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. © 2012 IEEE.
- Publisher
- Beijing IEEE
- Rights
- Copyright 2012 IEEE
- Rights
- This metadata is freely available under a CCO license
- Subject
- Data mining; Health informatics; Law; Traditional Chinese Medicine
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