A residual-convolution-recurrent network with K-margin segment selection and voting achieves 0.8125 F1NAOP on the PhysioNet 2017 atrial fibrillation benchmark.
Real-time ecg monitoring and arrhythmia detection using android-based mobile devices
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SP 1years
2019 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection
A residual-convolution-recurrent network with K-margin segment selection and voting achieves 0.8125 F1NAOP on the PhysioNet 2017 atrial fibrillation benchmark.