Deep learning based heart disease prediction
Data mining is the process of data analyzing from
various perspectives and combining it into useful information.
This technique is used for finding heart disease. Based on risk
factor the heart diseases can be defined very easily. The main aim
of this work is to evaluate different classification techniques in
heart diagnosis. First, the ECG numeric dataset is extracted and
preprocess them. After that using extract the features that is
condition to be find to be classified by Convolution Neural
Network (NN).Compared to existing; Convolution Neural
Network provides better performance. After classification,
performance criteria including accuracy, precision, F-measure is
to be calculated. Compared to KNN, Convolution Neural
Network provides better performance. The comparison measure
expose that Convolution Neural Network is the best classifier for
the diagnosis of heart disease on the existing dataset.
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Network-Based Automated ECG Signal Classifier”, 29 May2013.
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Classification of ECG Signal for Heart Disease Diagnosis using
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Different Heart Diseases Based On Neural Network Classification”.
ISSN 0973-4562 Volume 11, Number 6 (2016) pp3859-3864.
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