IJCATR Volume 7 Issue 7

Prediction of Heart Disease in Diabetic patients using Naive Bayes Classification Technique

Charu V.Verma , Dr. S. M. Ghosh
10.7753/IJCATR0707.1002
keywords : Heart Disease, Diabetes, Data Mining, KDD, Naïve Bayes.

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The objective of our paper is to predict the risk of heart disease in diabetic patients. In this research paper we are applying Naive Bayes data mining classification technique which is a probabilistic classifier based on Bayes theorem with strong (naive) independence assumptions between the features. Data mining techniques have been widely used in health care systems for prediction of various diseases with accuracy. Health care industry contains large amount of data and hidden information. Effective decisions are made with this hidden information by applying data mining techniques. These techniques are used to discover hidden patterns and relationships from the datasets. The major challenge facing the healthcare industry is the provision for quality services at affordable costs. A quality service implies diagnosing patients correctly and treating them effectively. In this proposed system certain attributes are consider in diabetic patients to predict the risk of heart disease
@artical{c772018ijcatr07071002,
Title = "Prediction of Heart Disease in Diabetic patients using Naive Bayes Classification Technique",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "7",
Issue ="7",
Pages ="241 - 269",
Year = "2018",
Authors ="Charu V.Verma , Dr. S. M. Ghosh"}