![]() ![]() This includes Alzheimer’s dementia, diabetic retinopathy, and brain hemorrhage, among others. Deep learning in COVID-19 diagnosisĭeep learning has been extensively employed in medical imaging over the past decade, and intensive efforts have enabled it to deliver highly accurate reports in many conditions. The detection of lung consolidation in combination with laboratory and clinical assessments could be useful in diagnosing this disease early and reliably. As the condition becomes more severe, these markings become invisible, or ‘whited-out’. ![]() The typical radiographic appearance of the lungs in COVID-19 pneumonia is of ground-glass opacities and sometimes of linear opacities in the lung periphery, with the lung markings being somewhat obscured. Important findings in this condition include increased whiteness of the lungs, proportional to the severity of the disease. Thus, chest X-rays play a large part in the diagnosis of COVID-19 pneumonia. Image Credit: Chest X-rays in COVID-19ĬOVID-19 affects the lungs, primarily, although it can damage multiple organs in severe or critical disease. This preprint, available on the medRxiv* server, presents experimental results that suggest a high-performing approach for COVID-19 diagnostic radiography.Įxamples of frontal-view chest X-Ray images from the datasets. The rapid diagnosis of coronavirus disease 2019 (COVID-19) is a high research priority, with the rapid increase in infections and deaths as winter approaches.Ī new study from Athens, Greece, describes the use of a deep learning algorithm that uses chest X-rays to diagnose COVID-19 pneumonia. ![]()
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