Data Mining Techniques for Heart Disease Prediction: A Computational Model

Data has risen as new capital in this digital age, in which everything is being transposed into the electronic domain. The manner in which such data is stored and used for an effective purpose will make data the most valuable resource for any organization. Data analytics is used in medical and healthcare industries to predict disease. Identification of the links between the tremendous databases. The objective of this work is to check for the presence of heart disease with specific features in the data sets. We use classification algorithms such as Support Vector Classifier (SVC), Naive Bayes (NB), Decision Tree (DT), Random Forest to predict heart disease perception with specific characteristics. The effective technique with highest accuracy will help the heart specialists around the globe, especially in developing countries and resource constrained regions.