Classification of ECG using ensemble of residual CNNs with or without attention mechanism

. This paper introduces a winning solution (team ISIBrno-AIMT) to the official round of PhysioNet Challenge 2021. The main goal of the challenge was a classification of ECG recordings into 26 multi-label pathological classes with a variable number of leads (e.g. 12, 6, 4, 3, 2). The main objective o...

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Veröffentlicht in:	Physiological measurement 2022-04, Vol.43 (4), p.44001
Hauptverfasser:	Nejedly, Petr, Ivora, Adam, Viscor, Ivo, Koscova, Zuzana, Smisek, Radovan, Jurak, Pavel, Plesinger, Filip
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms attention mechanism classification deep learning ECG Electrocardiography - methods Entropy PhysioNet challenge 2021 Probability
Online-Zugang:	Volltext
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