Convolutional neural network detects COVID-19 from chest radiography images

摘要

Those keeping up with the news know that coronavirus testing helps track and stop the spread of the virus. In countries like the United States, testing remains behind where it should be, largely as a result oflack of tests and the tremendous burden placed on the national healthcare system. A new, open-source deep learning-based COVID-19 testing method offers hope in the form of an accurate, fast technique. Caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the COVID-19 pandemic continues to devastate the health and well-being of the global population. While the main screening method- polymerase chain reaction (PCR) testing-detects SARSCoV-2 RNA from respiratory specimens reliably, it is a time consuming, laborious, and complicated manual process in short supply. Chest radiography imaging like X-ray or computed tomography (CT) provide radiologists visual indicators associated with the SARS-CoV-2 viral infection, as early studies show patients present abnormalities in chest radiography images characteristic of those infected with COVID-19, with some suggesting that radiography examination could be used as a primary tool for COVID-19 screening in epidemic areas.