Heart Attack Prediction using Artificial Neural Networks

To predict and identify patients with heart disease, we used various artificial neural networks (ANN) such as Single Layer Perceptron, Multilayer Perceptron, Radial Basis Function and Long Short-Term Memory (Recurrent neural network). The proposed model's strength was very satisfying, as it was able to predict evidence of developing heart disease in a given person using RBF and MLP, which demonstrated a high degree of precision as opposed to other used methods such as LSTM. The given heart disease prediction system improves medical care and reduces the cost.