COMBINED METHODOLOGY of the CLASSIFICATION RULES for MEDICAL DATA - SETS
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2012 by IJETT Journal|
|Year of Publication : 2012|
|Authors : V.Sneha Latha , P.Y.L.Swetha , M.Bhavya , G. Geetha , D. K.Suhasini|
V.Sneha Latha , P.Y.L.Swetha , M.Bhavya , G. Geetha , D. K.Suhasini. "COMBINED METHODOLOGY of the CLASSIFICATION RULES for MEDICAL DATA - SETS". International Journal of Engineering Trends and Technology (IJETT). V3(1):32-36 Jan-Feb 2012. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
‘Data mining’ offers methodological and technical solutions to deal with the analysis of medical data and construction of prediction models. A large variety of these methods requires general and simple guidelines that may help prac titioners in making clinical decisions. The purpose of this study was to build a hybrid data mining model to extract classification knowledge for various health hazards to aid in clinical decisions in an emergency department. This study utilized real world data collected from an emergenc y department of a hospital and used a new model which is developed combining the Apriori algorithm and a C5.0 algorithm to generate a classification rule base for the classification of medical data - sets, which can help physi cians to make clinical decisions faster and more accurately
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Data mining, chest pain, clinical decisions, emergency department, Hybrid model.