Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
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.
How to cite this article:
A. Lourdu Caroline and S. Manikandan. A Data Mining Technique for Prediction of Chest Pain using Medical
Laboratory Dataset.
DOI: https://doi.org/10.36478/jeasci.2017.920.928
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2017.920.928