Automated arrhythmia classification based on a pyramid dense connectivity layer and BiLSTM
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DOI: 10.1177/09287329241290941
Abstract: Background Deep neural networks (DNNs) have recently been significantly applied to automatic arrhythmia classification. However, their classification accuracy still has room for improvement. Objectives The aim of this study is to address the existing limitations… read more here.
Keywords: classification; connectivity layer; arrhythmia classification; dense connectivity ... See more keywords