Cardio Vascular Disease Classification Ensemble Optimization using Genetic Algorithm and Neural Network

Jagwant Singh  and Rajinder Kaur

doi:10.17485/ijst/2016/v9i(S1)/98900

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Cardio Vascular Disease Classification Ensemble Optimization using Genetic Algorithm and Neural Network

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2016/v9i(S1)/98900

Year: 2016, Volume: 9, Issue: Special Issue 1, Pages: 1-5

Original Article

Cardio Vascular Disease Classification Ensemble Optimization using Genetic Algorithm and Neural Network

Jagwant Singh¹ and Rajinder Kaur²

Department of Computer Science Engineering, Chandigarh University, Gurgoan – 140413, Punjab, India; [email protected]
[email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Objective: To develop a new technique for the detection of heart disease and to build the detection system based on fuzzy logic algorithm for extraction of features by applying neural network classifier of heart disease. Methods/Statistical analysis: The disease dataset is classified by using Fuzzy logic, genetic algorithm and training is done by neural network by the extracting features. The image is tested on the basis of features of dataset and the extracted images. Findings: The accuracy is improved up to 99.97%. The error rate is reduced, it is .987 %. Application/Improvements: This paper presented the ECG signal modeling along with classification of diseases using fuzzy logic, Genetic Algorithm and Neural Network with improved accuracy and less error rate.
Keywords: Accuracy, Error Rate, Fuzzy Logic, Genetic Algorithm, Heart Disease, Neural Network