Diagnosis of Heart Failure Using AI Techniques

Human body contains many organs, but one of the prime organs is the heart, which is a network of vessels which help the blood to flow into our body. Cardiovascular disease is any disturbance in the heart's normal functioning or performance. In this work, closely worked with heart disease prediction and for that, the team will be looking into the heart disease dataset from where work will be derived various perceptions that help us to know the value of each feature and their connections. Also, here the aim is to detect the possibility of a person be affected by a savior heart disease or not. This research paper presents various algorithms of machine learning by which a projection of heart disease can be made and required steps can be taken as early as possible for prevention. This paper consists of five algorithms (SVM, Decision Tree, K-NN, Ensemble Method and ANN) which are applied to the dataset that is publicly available. On applying Ensemble Method (combination of K-NN, Decision Tree, and SVM) on the dataset an accuracy of 89.88% was attained. ANN was able to outperform all the other algorithms with accuracy of 95.33%.