Detection and localization of myocardial infarction based on a convolutional autoencoder

Twelve-lead electrocardiograms (ECG) are widely used for the diagnosis of myocardial infarction (MI). For MI detection and localization, 12 ECG signals should be comprehensively checked through visual observation. This process is time-consuming, requires significant effort, and is prone to inducing...

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Veröffentlicht in:	Knowledge-based systems Jg. 178; S. 123 - 131
Hauptverfasser:	Sugimoto, Kaiji, Kon, Yudai, Lee, Saerom, Okada, Yoshifumi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 15.08.2019 Elsevier Science Ltd
Schlagworte:	Cardiovascular diseases Classification Convolutional autoencoder Data Echocardiography Electrocardiogram Electrocardiography Errors Experiments Extraction False positive results Feature extraction Heart attacks Heart diseases k-nearest neighbor Localization Medical diagnosis Methods Myocardial infarction Patients Signal processing Ultrasonic imaging Visual observation Visual signals Waveforms Myocardial infarction k-nearest neighbor Convolutional autoencoder Electrocardiogram
ISSN:	0950-7051, 1872-7409
Online-Zugang:	Volltext
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