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
Link To Document :
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