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Prediction of COVID-19 using chest X-ray images

arXiv 2204.03849 ↗First posted 8 Apr 2022eess.IV cs.CVcited by 0

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Abstract (arXiv)

COVID-19, also known as Novel Coronavirus Disease, is a highly contagious disease that first surfaced in China in late 2019. SARS-CoV-2 is a coronavirus that belongs to the vast family of coronaviruses that causes this disease. The sickness originally appeared in Wuhan, China in December 2019 and quickly spread to over 213 nations, becoming a global pandemic. Fever, dry cough, and tiredness are the most typical COVID-19 symptoms. Aches, pains, and difficulty breathing are some of the other symptoms that patients may face. The majority of these symptoms are indicators of respiratory infections and lung abnormalities, which radiologists can identify. Chest x-rays of COVID-19 patients seem similar, with patchy and hazy lungs rather than clear and healthy lungs. On x-rays, however, pneumonia and other chronic lung disorders can resemble COVID-19. Trained radiologists must be able to distinguish between COVID-19 and an illness that is less contagious. Our AI algorithm seeks to give doctors a quantitative estimate of the risk of deterioration. So that patients at high risk of deterioration can be triaged and treated efficiently. The method could be particularly useful in pandemic hotspots when screening upon admission is important for allocating limited resources like hospital beds.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 10 of its 27 references that are in the map. First posted on arXiv 8 Apr 2022.

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References · 10

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  3. 2020COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-Ray Imagescited by 264
  4. 2020COVID-19 Image Data Collectioncited by 100
  5. 2020COVID-CT-Dataset: A CT Scan Dataset about COVID-19cited by 93
  6. 2020CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray imagescited by 68
  7. 2018Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classificationcited by 57
  8. 2020Rapid AI Development Cycle for the Coronavirus (COVID-19) Pandemic: Initial Results for Automated Detection & Patient Monitoring using Deep Learning CT Image Analysiscited by 38
  9. 2017SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rayscited by 12
  10. 2017Deep Learning with Lung Segmentation and Bone Shadow Exclusion Techniques for Chest X-Ray Analysis of Lung Cancercited by 10

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