AI system bests radiologists in spotting COVID-19 in lungs

A new artificial intelligence (AI) platform developed by Northwestern University researchers can detect COVID-19 in the lungs 10 times faster and a bit more accurately than specialized cardiothoracic radiologists, according to a study published today in Radiology. The researchers trained and tested DeepCOVID-XR, a machine-learning algorithm that analyzes chest X-rays, on 17,002 X-ray images, 5,445 of them with signs of COVID-19, collected from February to April. When pitted against five experienced cardiothoracic radiology subspecialists, DeepCOVID-XR analyzed each of 300 randomly selected test images in about 18 minutes, versus the 2.5 to 3.5 hours of individual radiologists. DeepCOVID-XR was 82% accurate, compared with the radiologists' 76% to 81% individually and 81% as a team. "These are experts who are sub-specialty trained in reading chest imaging, whereas the majority of chest X-rays are read by general radiologists or initially interpreted by non-radiologists, such as the treating clinician," lead author Ramsey Wehbe, MD, said in a Northwestern news release.