COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images
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Abstract
The Coronavirus Disease 2019 (COVID-19) pandemic continues to have a devastating effect on the health and well-being of the global population. A critical step in the fight against COVID-19 is effective screening of infected patients, with one of the key screening approaches being radiology examination using chest radiography. It was found in early studies that patients present abnormalities in chest radiography images that are characteristic of those infected with COVID-19. Motivated by this and inspired by the open source efforts of the research community, in this study we introduce COVID-Net, a deep convolutional neural network design tailored for the detection of COVID-19 cases from chest X-ray (CXR) images…
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3Topics & keywords
Topics
Keywords
- Coronavirus disease 2019 (COVID-19)
- Convolutional neural network
- Computer science
- Benchmark (surveying)
- Radiography
- Audit
- Pandemic
- Artificial intelligence
UN Sustainable Development Goals
- Good health and well-being
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