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Machine Learning Techniques Applied to Data Analysis and Anomaly Detection in ECG Signals

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Sanjeev Kumar Saini & Rashmi Gupta. (2021) Artificial intelligence methods for analysis of electrocardiogram signals for cardiac abnormalities: state-of-the-art and future challenges. Artificial Intelligence Review 55:2, pages 1519-1565.
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Peng Zhan, Haoran Xu & Lin Chen. (2020) FCAD: Feature-based Clipped Representation for Time Series Anomaly Detection. FCAD: Feature-based Clipped Representation for Time Series Anomaly Detection.
Tomasz Andrysiak. (2018) Sparse representation and overcomplete dictionary learning for anomaly detection in electrocardiograms. Neural Computing and Applications 32:5, pages 1269-1285.
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Rostom Mennour & Mohamed Batouche. 2020. Deep Learning and Neural Networks. Deep Learning and Neural Networks 633 653 .
Rostom Mennour & Mohamed Batouche. (2018) Novel Scalable Deep Learning Approaches for Big Data Analytics Applied to ECG Processing. International Journal of Applied Metaheuristic Computing 9:4, pages 33-51.
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Huorong Ren, Xiujuan Liao, Zhiwu Li & Abdulrahman AI-Ahmari. (2017) Anomaly detection using piecewise aggregate approximation in the amplitude domain. Applied Intelligence 48:5, pages 1097-1110.
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Tomasz Andrysiak. 2018. International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding. International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding 428 438 .

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