Paper Key : IRJ************975
Author: Bhor Kalyani Kisan
Date Published: 07 Apr 2024
Abstract
Heart attacks are a dangerous condition that have become more common in recent years. This could be because the number of elderly people worldwide is rising, which weakens the heart muscle. However, with prompt diagnosis and efficient treatment, these heart conditions can be successfully avoided. But due to the large-scale complexity that is achieved in the detection of cardiac disease is this requires a lot of time which the patient might not have. Therefore, by using a patient's qualities, this approach effectively predicts a patient's cardiac condition, improving the diagnostic process and helping the cardiac expert and the implementation of deep learning approaches. The methodology proposed in this research for the purpose of heart disease prediction implements Pearson Correlation along with Artificial Neural Networks and Decision Making for accurate heart disease prediction. The performance metrics of this approach have been thoroughly evaluated through experimental evaluation in this research to achieve highly satisfactory outcomes.