Deep learning based heart disease prediction

  • Ashwini Phalke
  • Shanta Sondur

Abstract

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.

Keywords: Data mining, Heart diagnosis, Convolution Neural Networks (CNN).

References

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How to Cite
Phalke, A., & Sondur, S. (2019). Deep learning based heart disease prediction. Asian Journal For Convergence In Technology (AJCT). Retrieved from http://www.asianssr.org/index.php/ajct/article/view/787
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