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Data Mining Classification Techniques Applied For Cancer Disease A Case Study Using Xlminer


Data Mining Classification Techniques Applied For Cancer Disease  A  Case Study Using Xlminer
Authors : S. Jothi, S.Anita
Publication Date: 29-10-2012

Authors

Author(s):  S. Jothi, S.Anita

Published in:   International Journal of Engineering Research & Technology

License:  This work is licensed under a Creative Commons Attribution 4.0 International License.

Website: www.ijert.org

Volume/Issue:   Vol.1 - Issue 8 (October - 2012)

e-ISSN:   2278-0181

Abstract

Data mining techniques have been used in medical research for many years and have been known to be effective. In order to solve such problems as long-waiting time, congestion, and delayed patient care, faced by emergency departments, this study concentrates on building a hybrid methodology, combining data mining techniques such as association rules and classification trees. The methodology is applied to real-world emergency data collected from a hospital and is evaluated by comparing with other techniques. The methodology is expected to help physicians to make a faster and more accurate classification of cancer diseases.

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