@article{MAKHILLJEAS201712414193,
    title = {A Data Mining Technique for Prediction of Chest Pain using Medical
Laboratory Dataset},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {12},
    number = {4},
    pages = {920-928},
    year = {2017},
    issn = {1816-949x},
    doi = {jeasci.2017.920.928},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2017.920.928},
    author = {A. Lourdu and},
    keywords = {Data mining,medical decisions,medical domain knowledge,chest pain,combining},
    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.}
    }