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Title: Biomedical Neural Network application for heart disease detection and accuracy enhancement using Genetic Algorithm

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Title:
Biomedical Neural Network application for heart disease detection and accuracy enhancement using Genetic Algorithm
Author Name:
Ms. Preeti Gupta, Dr. Bikrampal Kaur
Abstract:
Heart diagnosis equipments are not always available in every medical center, especially in rural areas. Doctor’s intuition and experience are not always enough to attain high quality medical results therefore, correct diagnosis is must before performing proper treatments for heart disease. Many researchers have proposed machine learning based approaches to improve the accuracy of heart disease diagnosis. The goal of this study is to develop heart disease diagnosis system based on the hybridization of Genetic Algorithm with Neural Network. Hybridization has applied to train the neural network using Genetic Algorithm and proved experimentally. The trained feed forward neural network and fitting neural network are optimized with genetic algorithm and is then compared with the feed forward neural network and fitting neural network respectively for the accuracy enhancement percentage. The proposed learning is much faster and accurate as compared to the other one. The dataset used is the Cleveland Heart Database taken from the UCI learning data set repository. The proposed learning is designed and developed by using MATLAB GUI feature. The proposed method achieved an accuracy of 97.75%. With this higher achieved accuracy the heart disease can be diagnosed more accurately and much proper treatments can be suggested.
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