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Titel:

DWT-CNNTRN: a Convolutional Transformer for ECG Classification with Discrete Wavelet Transform.

Dokumenttyp:
Journal Article; Research Support, Non-U.S. Gov't
Autor(en):
Zou, Congyu; Djajapermana, Mikhael; Martens, Eimo; Muller, Alexander; Ruckert, Daniel; Muller, Phillip; Steger, Alexander; Becker, Matthias; Wolfgang, Utschick
Abstract:
Cardiovascular diseases are the leading cause of death worldwide. The diagnoses of cardiovascular diseases are usually carried out by cardiologists utilizing Electrocardiograms (ECGs). To assist these physicians in making an accurate diagnosis, there is a growing need for reliable and automatic ECG classifiers.In this study, a new method is proposed to classify 12-lead ECG recordings. The proposed model is composed of four components: the CNN(Convolutional Neural Network) module, the transformer...     »
Zeitschriftentitel:
Annu Int Conf IEEE Eng Med Biol Soc
Jahr:
2023
Band / Volume:
2023
Seitenangaben Beitrag:
1-6
Volltext / DOI:
doi:10.1109/EMBC40787.2023.10340561
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/38082682
Print-ISSN:
2375-7477
TUM Einrichtung:
Institut für KI und Informatik in der Medizin (Prof. Rückert); Klinik und Poliklinik für Innere Medizin I, Kardiologie (Prof. Laugwitz)
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