TY  - JOUR
T1  - A Data Mining Technique for Prediction of Chest Pain using Medical
Laboratory Dataset
AU - Caroline, A. Lourdu AU - Manikandan, S. 
JO  - Journal of Engineering and Applied Sciences
VL  - 12
IS  - 4
SP  - 920
EP  - 928
PY  - 2017
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2017.920.928
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2017.920.928
KW  - Data mining
KW  -medical decisions
KW  -medical domain knowledge
KW  -chest pain
KW  -combining
AB  - 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.
ER  -