Recommendation of attributes for heart disease prediction using correlation measure

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Abstract

Heart diseases are the major cause for human mortality rate. Correct diagnosis and treatment at an early stage will save people from heart disease and will decrease mortality rate due to heart problem. Since ten years various data mining techniques have been used to facilitate the prediction of heart diseases.In general prediction algorithms for trained with huge, known dataset to arrive at a classifier which then predicts the diseases for unknown data with the help of classifying attributes. These attributes also called as features. In this work relevant features are determined for heart disease prediction with known dataset using correlation measures. The results are presented.

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Chellammal, S., & Sharmila, R. (2019). Recommendation of attributes for heart disease prediction using correlation measure. International Journal of Recent Technology and Engineering, 8(2 Special issue 3), 870–875. https://doi.org/10.35940/ijrte.B1163.0782S319

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