Artificial Neural Networks based Distributed Approach for Heart Disease Prediction

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A recent study shows that almost 30% of total global deaths are caused by heart disease. These days precise diagnosis related to heart disease is very difficult. The doctor advises patients to take various tests for diagnosis, which is a very costly and time-consuming process as medical databases are large and cannot be processed quickly. A new approach has been proposed to predict heart disease from historical data sets. In this chapter, heart disease possibilities in patients are predicted with the help of neural networks on distributed computing. Feature selection was applied to the dataset to get better results and to increase the performance. Feature selection reduces the number of attributes from the dataset and only provides the necessary attributes, which directly reduces the number of tests required for the diagnosis. nbsp;