AI can detect COVID-19 in the lungs like a virtual physician, new study shows

The new UCF co-developed algorithm can accurately identify COVID-19 cases, as well as distinguish them from influenza. ORLANDO, Sept. 30, 2020 - A University of Central Florida researcher is part of a new study showing that artificial intelligence can be nearly as accurate as a physician in diagnosing COVID-19 in the lungs. The study, recently published in Nature Communications, shows the new technique can also overcome some of the challenges of current testing. Researchers demonstrated that an AI algorithm could be trained to classify COVID-19 pneumonia in computed tomography (CT) scans with up to 90 percent accuracy, as well as correctly identify positive cases 84 percent of the time and negative cases 93 percent of the time. CT scans offer a deeper insight into COVID-19 diagnosis and progression as compared to the often-used reverse transcription-polymerase chain reaction, or RT-PCR, tests.