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- W2953446736 abstract "The Electrocardiography classifier is an essential tool for helping doctors in diagnosing early heart problems. This paper proposes with an electrocardiography classifier for analyzing accuracy in case of non-long-tail effect. Data are obtained from MIT-BIH arrhythmia database. Therefore, a discrete wavelet transform decomposition algorithm is employed for feature extraction and a principal component analysis is used for dimension reduction of data. In addition, the heart beat can be classified using a neural network method. In order to evaluate the classifier accuracy, the confusion matrix and Receiver Operating Characteristic curve are applied." @default.
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- W2953446736 date "2019-06-06" @default.
- W2953446736 modified "2023-10-10" @default.
- W2953446736 title "Design of Classifier for Electrocardiography Classification" @default.
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- W2953446736 doi "https://doi.org/10.1007/978-981-13-5859-3_83" @default.
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