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Detecting COVID-19 from digitized ECG printouts using 1D convolutional neural networks. (arXiv:2208.05433v2 [eess.IV] UPDATED)
Oct. 6, 2022, 1:16 a.m. | Thao Nguyen, Hieu H. Pham, Huy Khiem Le, Anh Tu Nguyen, Ngoc Tien Thanh, Cuong Do
cs.CV updates on arXiv.org arxiv.org
The COVID-19 pandemic has exposed the vulnerability of healthcare services
worldwide, raising the need to develop novel tools to provide rapid and
cost-effective screening and diagnosis. Clinical reports indicated that
COVID-19 infection may cause cardiac injury, and electrocardiograms (ECG) may
serve as a diagnostic biomarker for COVID-19. This study aims to utilize ECG
signals to detect COVID-19 automatically. We propose a novel method to extract
ECG signals from ECG paper records, which are then fed into a one-dimensional
convolution neural …
arxiv convolutional neural networks covid covid-19 networks neural networks
More from arxiv.org / cs.CV updates on arXiv.org
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