@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}, }