1. Prediction of heart disease and strategic decision making for phi of medical dataset
Authors : Geetha Guttikonda, Sneha Cherukuri, Chandra Naga Sravanthy, Mohammad Irfanullah, Monica Korlapati
Pages : 45-50
DOI : http://dx.doi.org/10.21172/1.83.006
Keywords : Data mining, prediction, heart disease Abstract :Individuals take standard medical examinations for the most part not for finding virus but rather to have genuine feelings of serenity with respect to their wellbeing status. Along these lines, it is imperative to give them a general criticism as for all the wellbeing markers that have been positioned against the entire populace. Here, we propose a framework for prediction of heart disease for a taken dataset. Especially, the highest health risk is revealed in the cases of people who are having heart disease and not predicting it before hand. The huge amounts of data generated for prediction of heart disease are too complex and voluminous to be processed and analyzed by traditional methods. Data mining provides the methodology and technology to transform these mounds of data into useful information for decision making. By using data mining techniques it takes less time for the prediction of the disease with more accuracy.
Citing this Journal Article :Geetha Guttikonda, Sneha Cherukuri, Chandra Naga Sravanthy, Mohammad Irfanullah, Monica Korlapati, "Prediction of heart disease and strategic decision making for phi of medical dataset", Volume 8 Issue 3 - May 2017, 45-50
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