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- W3185314553 abstract "This paper aims at developing new techniques that study vital functions of the heart by analysing biological signals. ECG prediction is important for many current medical applications. Currently, there are many machine learning (ML) and deep learning (DL) solutions which are used for prediction of ECG data estimated in a period of time. We analyze the anomalies of the cardiac coherence model with an LSTM architecture with layers specifically designed to address the problem of long term dependency. Our method significantly outperforms the state of the art on the PhysioNet dataset." @default.
- W3185314553 created "2021-08-02" @default.
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- W3185314553 date "2021-05-01" @default.
- W3185314553 modified "2023-09-23" @default.
- W3185314553 title "The Analysis of biological signals using Machine Learning Techniques" @default.
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- W3185314553 doi "https://doi.org/10.1109/cscs52396.2021.00022" @default.
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