A new artificial intelligence platform detects COVID-19 by analyzing x-ray images of the lungs. Called DeepCOVID-XR, the machine-learning algorithm outperformed a team of specialized thoracic radiologists — spotting COVID-19 in x-rays about 10 times faster and 1–6 percent more accurately.
The researchers believe physicians could use the AI system to rapidly screen patients who are admitted into hospitals for reasons other than COVID-19. Faster, earlier detection of the highly contagious virus could potentially protect healthcare workers and other patients by triggering the positive patient to isolate sooner.
The study’s authors also believe the algorithm could potentially flag patients for isolation and testing who are not otherwise under investigation for COVID-19.
To develop, train, and test the new algorithm, the researchers used 17,002 chest x-ray images — the largest published clinical dataset of chest x-rays from the COVID-19 era used to train an AI system. Of those images, 5,445 came from COVID-19-positive patients from sites across the Northwestern Memorial Healthcare System.
The team then tested DeepCOVID-XR against five experienced cardiothoracic fellowship-trained radiologists on 300 random test images from Lake Forest Hospital. Each radiologist took approximately two-and-a-half to three-and-a-half hours to examine this set of images, whereas the AI system took about 18 minutes.