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- W2589835051 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." @default.
- W2589835051 created "2017-03-03" @default.
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- W2589835051 date "2016-01-20" @default.
- W2589835051 modified "2023-09-27" @default.
- W2589835051 title "Cardio Vascular Disease Classification Ensemble Optimization using Genetic Algorithm and Neural Network" @default.
- W2589835051 doi "https://doi.org/10.17485/ijst/2016/v9i(s1)/98900" @default.
- W2589835051 hasPublicationYear "2016" @default.
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