Data Mining Techniques to Construct a Model: Cardiac Diseases

Using echocardiography flexible Transthoracic Echocardiography reported data set detecting heart disease by using mining techniques designed prediction model the data set can develop the reliability of analysis of cardiac diseases by echocardiography, using eight iterative and interactive steps consisting Knowledge Discovery in Database (KDD) methodology including from 209 patients with echocardiography to extracting the data important mode of action Transthoracic Echocardiography inspection report. This study used data from Faisalabad Institute of Cardiology study from 2012 to 2015. All models exposed the results of J48 decision tree, naïve bayes classifier and neural network that has extraordinary classification precision and predictive of heart disease cases are generally comparable. However, J48 model predictive classification accuracy shows of 80% based on the true positive rate ratio and performance slightly better. This study shows to predict heart disease cases and People can be used the results of our study to make more consistent diagnosis of cardiac disease and to help them as a support tool for cardiac disease specialists. Keywords—Knowledge Discovery in Database (KDD); data mining; decision trees; neural networks; Bayesian classifier; heart