@article{(Open Science Index):https://publications.waset.org/pdf/10894,
	  title     = {A Hybrid Data Mining Method for the Medical Classification of Chest Pain},
	  author    = {Sung Ho Ha and  Seong Hyeon Joo},
	  country	= {},
	  institution	= {},
	  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 chest pain diseases.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {4},
	  number    = {1},
	  year      = {2010},
	  pages     = {99 - 104},
	  ee        = {https://publications.waset.org/pdf/10894},
	  url   	= {https://publications.waset.org/vol/37},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 37, 2010},