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- W4320063721 abstract "Abstract In computer visualization. Deep learning affords effective outcomes for machine learning complications. Several techniques like minimum distance technique, K-Nearest neighbor algorithm, Naïve Bayes, Support Vector Machine, and Artificial Neural Network are used for the purpose of medical data classification. In this paper, heart disease data classification is performed using convolutional neural network. Generally convolutional neural network uses and applied in image data sets, but, in proposed method is used to calculate the accuracy of event for heart disease data sets. The experiments are passed out using heart disease data set of Uel machine learning repository. This trained classifier can classify the given data into either normal or abnormal of heart disease data." @default.
- W4320063721 created "2023-02-12" @default.
- W4320063721 creator A5009501941 @default.
- W4320063721 date "2022-10-03" @default.
- W4320063721 modified "2023-09-25" @default.
- W4320063721 title "Heart Disease Prediction System Using Convolutional Neural Networks" @default.
- W4320063721 cites W2531733772 @default.
- W4320063721 doi "https://doi.org/10.21203/rs.3.rs-2009078/v2" @default.
- W4320063721 hasPublicationYear "2022" @default.
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