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Prediction of Heart disease using deep learning technique i.e. ANN-Artificial Neural Networks. The purpose of this project is to use a Neural networks models, which we are using for improving the accuracy of weak algorithms by combining a couple of classifiers.
Experiments with this approach were performed using a heart disease dataset. A comparative analytical approach had been executed to decide how the ANNs can be implemented for predicting accuracy in coronary heart ailment.
The purpose is not only to improve the accuracy of weak class algorithms, but additionally at implementing the algorithm with a clinical dataset, to predict the disease at an early level. Neural network models can be defined and evaluated using the Python Keras deep learning library.
Our framework was resulted in highly accurate fashions which are tailored for medical actual information and analysis use.
Our proposed model gives an increase of 2.5% accuracy than existing-model.