The fact that the disease can be detected more quickly, as well as coronavirus therapy and vaccine availability, is one of the issues scientists are working on. Using artificial intelligence in this area can also provide the results of the disease tests much more quickly. Linda Wang, Alexander Wong, and Canadian-based artificial intelligence company DarwinAI, from Waterloo University, who worked to use artificial intelligence to diagnose coronavirus, developed an artificial intelligence called COVID-Net. COVID-Net is able to detect symptoms of the disease on chest x-rays of people with coronavirus. For the development of COVID-Net, a data set was created from 5,941 x-ray images of the patient who had 2,839 viral and bacterial infections. Artificial intelligence can detect the symptoms of coronavirus in the lung using this data set. Researchers also offer the data set to those who want to use artificial intelligence called COVID-Net. In this way, the data set can be changed by users or artificial intelligence can be developed by adding new data to the data set. DarwinAI’s CEO, Sheldon Fernandez, says that COVID-Net is not yet fully available for use in disease detection. The CEO invites researchers to support the study so that artificial intelligence can perform reliable coronavirus tests. Rapid testing of large masses is an important issue in these days when coronavirus infects more than 375,000 people in 195 countries. The use of artificial intelligence in the detection of coronavirus and its successful results can lead to the application of coronavirus tests to more people.
