DeepCOVID-XR is a Northwestern University developed algorithm that automatically detects the signs of COVID-19 on a basic X-ray of the lungs. The system is able to detect COVID-19 in X-rays 10 times faster than thoracic radiologists and 1% to 6% more accurately.
The developers said the AI could be used to rapidly screen patients at hospital admission, and trigger protocols to help protect healthcare workers.
Accoring to Professor Aggelos Katsaggelos, the alorithm will not replace testing, but will enable the use of cheap, routine, safe x-rays to determine if a patient needs to be isolated.
In 17,000 X-ray images, the algorithm identified lungs which appeared patchy and hazy, as air sacs became inflamed and filled with fluid instead of air, which is common in COVID-19.
When put up against five experienced, fellowship-trained radiologists, DeepCOVID-XR was able to process a set of 300 test X-rays in about 18 minutes, compared to about two and a half to three and a half hours. The AI also delivered an accuracy rate of 82%, about on par with the group’s range of 76% to 81%.
“Radiologists are expensive and not always available,” Katsaggelos said. “X-rays are inexpensive and already a common element of routine care. This could potentially save money and time—especially because timing is so critical when working with COVID-19.”