Heart Disease Prediction Using Modified K-Means and Using Naive Baiyes

Authors

  • Mujawar S Dept. of Information Technology, BVDUCOE, Pune, Maharashtra, India
  • Devale P Dept. of Information Technology, BVDUCOE, Pune, Maharashtra, India

Keywords:

Naive Baiye, Decision Tree, Data mining, Classification, Clustering

Abstract

The health care industry is generally rich in information which is not feasible to handle manually. These large amounts of data are very important in the field of Data Mining to extract useful information and generate relationship amongst the attributes. In the health care industry, for predicting the diseases from the datasets data mining is used. Heart disease prediction is treated as most complicated task in the field of medical sciences. This paper investigates a number of techniques in the detection of heart disease. This paper includes a blueprint of application of data mining in heart disease prediction.

References

Jesmin Nahar, Tasadduq Imam, and Kevin S.Tickle, “Computational intelligence for heart disease diagnosis: A medical knowledge driven approach”, Elsevier Ltd, 2012.

Sivagowry .S, Dr. Durairaj. M,Persia.A, “An Empirical Study on applying Data Mining Techniques for the Analysis and Prediction of Heart Disease”, IEEE, 2013.

M.Akhil jabbar,B.L Deekshatulua ,Priti Chandra, “Classification of Heart Disease Using K-Neighbor and Genetic Algorithm, CIMTA”, Elsevier Ltd,2013

Ankita Dewan,Meghna Sharma,”Prediction of Heart Disease using Hybrid Technique in Data Mining Classification”,IEEE,2015.

Jyothi Soni, Uzma ansari and Dipesh Ansariss “Intelligent and Effective Heart Disease Prediction System using Weighted Associate Classifer”, IJCSE, Vol 3(6), pp 2385-2392, June 2011.

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Published

2025-11-10

How to Cite

[1]
S. Mujawar and P. Devale, “Heart Disease Prediction Using Modified K-Means and Using Naive Baiyes”, Int. J. Comp. Sci. Eng., vol. 3, no. 10, pp. 76–78, Nov. 2025.

Issue

Vol. 3 No. 10 (2015): IJCSE October Edition

Section

Study Paper

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