Review of Data Mining Classification Models in Cardiovascular Disease Diagnosis

Medical science industry has huge amount of data, but unfortunately most of this data is not mined to find out hidden information in data. Advanced data mining techniques can be used to discover hidden pattern in data. Models developed from these techniques will be useful for medical practitioners to take effective decision. In this review paper data mining classification techniques RIPPER classifier, Decision Tree, Artificial neural networks (ANNs), and Support Vector Machine (SVM) are reviewed. In our research work we will compare these techniques through lift chart, error rate and will determine sensitivity, specificity, and accuracy of these data mining techniques.