We’ve seen artificial intelligence (AI) detect different cancers, kidney illness, and brain tumors. Now, researchers from Mount Sinai believe they are the first in the US to use AI, combined with imaging and clinical data, to diagnose COVID-19. In a paper published in Nature Medicine today, they explain how they used CT scans of the chest — along with symptoms, age, bloodwork, and possible contact with the virus — to spot the coronavirus disease.
“We were able to show that the AI model was as accurate as an experienced radiologist in diagnosing the disease, and even better in some cases where there was no clear sign of lung disease on CT,” said one of the lead authors, Zahi Fayad.
The researchers note that scans don’t always show lung diseases when a patient first presents symptoms and lab tests can take days to come back. The AI helps address both of those problems as the AI model can provide a ‘second opinion’ to physicians when a CT scan turns up negative or shows nonspecific findings, which is quite common.
The researchers trained the algorithm on over 900 scans from medical centers in China. The scans included 419 confirmed COVID-19 cases and 486 negative cases. Researchers also had access to clinical information, like blood test results showing abnormalities in white blood cell counts or lymphocyte counts.
The algorithm they created mimics a workflow a physician would use to diagnose COVID-19. It produces separate probabilities of being COVID-19 positive based on CT images, clinical data, and both combined. Next, the researchers hope to find clues about how well patients will do based on subtleties in their CT data and clinical information.
While CT scans aren’t widely used to diagnose COVID-19 in the US, the team believes they have the potential to play an important role. Eventually, the AI could be used in hospitals around the world.