Anomaly Electrocardiograms Automatic Detection with Unsupervised Deep Learning Methods

Eugene Yu. Shchetinin; Anastasia G. Glushkova; Leonid A. Sevastianov

doi:10.1007/978-3-031-23207-7_10

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Anomaly Electrocardiograms Automatic Detection with Unsupervised Deep Learning Methods

Eugene Yu. Shchetinin Anastasia G. Glushkova Leonid A. Sevastianov

Year: 2022 Lecture notes in computer science Pages: 117-131 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-031-23207-7_10

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Keywords:

Autoencoder Computer science Artificial intelligence Anomaly detection Support vector machine Pattern recognition (psychology) Precision and recall Deep learning F1 score Random forest Artificial neural network Machine learning Data mining

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1.09

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0.81

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Citation History

Topics

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

ECG Monitoring and Analysis

Health Sciences → Medicine → Cardiology and Cardiovascular Medicine

Imbalanced Data Classification Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Anomaly Electrocardiograms Automatic Detection with Unsupervised Deep Learning Methods

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Citation History

Topics

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