ANALYSIS OF HEART ATTACK PREDICTION USING VARIOUS PARAMETERS
Paper Key : IRJ************968
Author: Bhoomika H R
Date Published: 02 Sep 2022
Heart attack is one of the most heinous attacks, especially the silent heart attack, which attacks a person so abruptly that theres no time to get it treated and such attack is very difficult to be diagnosed. The number of specialist doctors and an increase in wrong diagnosed cases have necessitated the need for building an efficient heart attack detection system. Various medical data mining and machine learning techniques are being implemented to extract valuable information regarding heart attack prediction. Yet, the accuracy of the desired results is not satisfactory. In this project, we propose a heart attack prediction system using Deep learning techniques, specifically Recurrent Neural Network to predict the likely possibilities of heart-related attacks of the patient. Recurrent Neural Network is a very powerful classification algorithm that makes use of the Deep Learning approach in Artificial Neural Network. The project discusses in detail the major modules of the system along with the related theory. The proposed model incorporates deep learning and data mining to provide accurate results with minimum errors. This project provides a direction and precedent for the development of a new breed of heart attack prediction platform.