Heart Disease and Diabetes Prediction Using Data Mining |
Author(s): |
| Tanmay Tamhane , Rajiv Gandhi Institute of Technology, Mumbai; Mateen Shaikh, Rajiv Gandhi Institute of Technology, Mumbai; Prof. Abhay Patil, Rajiv Gandhi Institute of Technology, Mumbai; Sanjaykumar Boga, Rajiv Gandhi Institute of Technology, Mumbai; Mrunal Tanwar, Rajiv Gandhi Institute of Technology, Mumbai |
Keywords: |
| Naive Bayesian, WAC (Weighted Associative Classifier, Heart Disease, Diabetes, Data Mining |
Abstract |
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The healthcare industry collects huge amounts of health related data which, unfortunately, is not ‘mined’ to discover hidden information for effective decision making. Discovery of hidden patterns and their relationships often goes undetected. Advanced data mining techniques can help remedy this situation. Our project describes about using data mining techniques, namely Naive Bayesian and WAC (Weighted Associative Classifier).In our system, we will store patients’ health record details and update it on that patient’s regular visits. The doctor will check the patient’s record from time to time. And, based on the results shown by our system, the doctor will come to know the occurrence of a disease in future. |
Other Details |
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Paper ID: IJSRDV3I1536 Published in: Volume : 3, Issue : 1 Publication Date: 01/04/2015 Page(s): 1052-1054 |
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