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Prediction of Heart Disease using Soft Computing and Data Mining
K.Sudhakar,  Dr. M. Manimekalai
Cardiovascular disease (CVD) has become the primary killer worldwide and is expected to cause more deaths in the future. Prediction and prevention of CVD have therefore become important social problems. Many groups have developed prediction models for asymptomatic CVD by classifying its risk based on established risk factors (e.g., age, sex, etc.). The growth of medical databases is very high. This rapid growth is the main motivation for researchers to mine useful information from these medical databases. As the volume of stored data increases, data mining techniques play an important role in finding patterns and extracting knowledge to provide better patient care and effective diagnostic capabilities. In the proposed system, the genetic algorithm was first used to reduce the number of attributes that are needed for predicting the cardiovascular disease and then the neural network was employed for prediction of disease from the reduced set of attributes.
Keywords- Cardiovascular Disease, Data Mining, Genetic Algorithm, Neural Networks
Unique Identification Number - IJEDR1404097Page Number(s) - 3985-3989Pubished in - Volume 2 | Issue 4 | Dec 2014DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
K.Sudhakar,  Dr. M. Manimekalai,   "Prediction of Heart Disease using Soft Computing and Data Mining"
, International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.2, Issue 4, pp.3985-3989, Dec 2014, Available at :http://www.ijedr.org/papers/IJEDR1404097.pdf