Heart disease prediction using convolutional neural network

The computational method presented in this chapter is based on deep learning and uses a convolutional neural network (CNN). Using CNN, we can develop an appropriate methodology and implement those methods to develop a prediction-based method that can provide pertinent and valuable information and act as a helping body for researchers and radiologists in diagnosis, treatment, and prevention of heart disease. This chapter is anticipated to help researchers, students, and practitioners related to medical diagnosis of computer science in how to implement deep learning-based methods for disease prediction. It gives the idea of CNN, which involves a deep learning approach, especially used in image processing and understanding or classification of images. The developed model classifies heart disease-related medical images with the help of CNN with an accuracy of ~96%. This model is developed in TensorFlow, a Google Python-based library used for the deep learning-based tasks.