Review on Prediction System for Heart Diagnosis Using Data Mining Techniques
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2015, Vol 17, Issue 5
Abstract
Abstract: Data mining is the process of analyzing large sets of data and then extracting the meaning of the data. It helps in predicting future trends and patterns, allowing business in decision making. Data mining applications can answer business questions that take much time to resolve traditionally. Large amount of data which is generated for the prediction of heart disease is analyzed traditionally and is too complicated and voluminous to be processed. Data mining provides the techniques and methods for the transformation of data into useful information for decision making. These techniques make the process fast and it takes less time for the prediction system to predict the heart disease with more accuracy. In this paper we survey different papers in which one or more algorithms of data mining used for the prediction of heart disease. Result from using neural networks is 99.62% in one paper [6] . By Applying data mining techniques to heart disease data which needs tobe processed, we can get effective results and achieve reliable performance which will help in decision making in healthcare industry. It will help the medical practitioners to diagnose the disease in less time and predict theprobable complications well in advance. Identifying the major risk factors of Heart Disease categorizing the risk factors in an order which causes damages to the heart such as high blood cholesterol, diabetes, smoking, poor diet, obesity, hyper tension, stress, etc. Data mining functions and techniques are used to identify the level of risk factors to help the patients in taking precautions in advance to save their life.
Authors and Affiliations
Divya kundra, , Er. Navpreet kaur
Keywords
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