Heart Disease Prediction System using Enhanced Apriori
P. Parameswari1, C. Ramachandran2, R. Rassika3
1Dr. P. Parameswari, Department of MCA, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
2Mr. C. Ramachandran, Department of MCA, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
3Ms. R. Rassika, Department of MCA, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 12 December 2018 | Revised Manuscript received on 23 December 2018 | Manuscript Published on 09 January 2019 | PP: 180-182 | Volume-7 Issue-4S November 2018 | Retrieval Number: E2029017519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Heart disease is frightening the people around the world and in some countries it is the number one disease which leads to death. Biomedical research efforts help to prevent and treat heart disease in a better way. Handling large amount of data is often very tedious with traditional methods which lead into problems, particularly in high level of complexity and vagueness factors. Mining frequent patterns from large databases has emerged as an important area in data mining research and knowledge discovery community; this also contributes so much to health care domain. This heart prediction system helps to predict heart related problems at an early stage. The proposed system predicts heart related issues of a person based on questions and the answers given to the prediction system. To have better results in minimum time duration an Enhanced Apriori algorithm was introduced which is an improvement of Apriori algorithm. The experimental results proved that the proposed approach performs faster and memory efficient with more number of patterns. It was also proved that the prediction rate of Enhanced Apriori was also good (94%) than Apriori (87%).
Keywords: Prediction, Data Mining, Heart Disease, Apriori, Association Rule Mining.
Scope of the Article: Regression and Prediction