Computational Approach for Cardiac Defect Detection using CNN Approach

Cardiac disease is one of the leading causes of death worldwide. Increased cashew consumption in India has been identified as one of the major variables responsible for the increased prevalence of the disease among the elderly in this region. This study aims to establish a classification of cardiovascular disease policy that includes cashew as a risk. This was done using 18,500 magnetic resonance imaging (MRI) data as a complement, and then the convolutional neural network method was trained to build the classification model. The model results considering accuracy and loss functions were evaluated, which reported 98.77% and 0.0100567, respectively, after ten years. The model was tested with other state-of-the-art algorithms, and the results showed that the new system is more reliable compared to others.