WASET
	%0 Journal Article
	%A Sung Ho Ha and  Seong Hyeon Joo
	%D 2010
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 37, 2010
	%T A Hybrid Data Mining Method for the Medical Classification of Chest Pain
	%U https://publications.waset.org/pdf/10894
	%V 37
	%X 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 chest pain diseases.
	%P 99 - 104