PREDICTIVE ANALYSIS OF DISEASE USING A-PRIORI AND K- MEAN TECHNIQUE
DOI:
https://doi.org/10.53555/eijse.v6i4.104Keywords:
Data mining, lung disease, heart disease, Apriority and K-means algorithmAbstract
Disease prognostication is one of the most important issues that we are facing today. A large number of patients struggle for their check-up even when it concerns of predictive diseases like heart attack possibilities, kidney damage and possibilities of lung problem. This motivates us to develop a hybrid algorithm which uses K-means and A-priori for data mining into large volumes of data and extract information that can be converted to useful knowledge and overall predict a patient for their chances of disease using a console. This console is developed with both algorithms working at back-end. This research paper is mainly focused on predicting lung and heart disease. Experimental results will show that many of the rules help in the best prediction of lung and heart disease, which even help doctors in their diagnostic decisions.
References
. Jyoti Soni, Sunitha Soni. Predictive data mining for Medical Diagnosis: An Overview of Heart Disease Prediction; International Journal of Compute Applications (0975-8887) Volume 17-No.8, March 2011.
. Fariba Shadabi, Dharmendra Sharma, Artificial Intelligence and Data Mining Techniques in Medicine-Success Stories, International Conference on Bio-Medical Engineering & Informatics, vol. 1, pp.235-239, 2008
. Bodon.F. A Fast A-priori Implementation, FIMI‟03, November 2003.
. Liao, S.C. and I.N. Lee, Appropriate medical data categorization for data mining classification techniques. MED. INFORM., 2002. Vol. 27, no. 1, 59–67.
. S.Vijiyarani, Disease Prediction in Data Mining Technique–ijcait, Vol. II, Issue I, January 2013 (ISSN: 2278-7720)
. My Chau Tu, Dongil Shin, Dongkyoo Shin, Effective Diagnosis of Heart Disease through Bagging Approach, 2nd International Conference on Biomedical Engineering and Informatics, 2009.
. M.Akhil Jabbar, Heart Disease Prediction System using Associative Classification and Genetic Algorithm. ICECIT, 2012
. N. Aditya Sundar, Performance analysis of classification data mining techniques over heart disease database, Volume-2, Issue-3, 470 – 478.
. C Y Hsu, J D Ordonez. The risk of acute renal failure in patients with chronic kidney disease. 2 April 2008
. Mohammed Abdul Khaleel, Sateesh Kumar Pradhan J Finding Locally Frequent Diseases Using Modified A-priori Algorithm, International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 10, October 2013.
. Chris Ding, Xiaofeng He,K-means Clustering via Principal Component Analysis, Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA 947208
. K.R. Lakshmi, Performance Comparison of Data Mining Techniques for Predicting of Heart Disease Survivability .International Journal of Scientific and Research Publications, Volume 3, Issue 6, June 2013.
. Lloyd, S. P. (1982). "Least squares quantization in PCM.IEEE Transactions on Information Theory28 (2): 129–137.
. R. Agrawal and R. Srikant-Fast algorithms for mining association rules. In 1994. pp. 487-49 VLDB'94, Santiago, Chile, Sept.1994. pp. 487-49.
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