Princeton AI machine shows promise in COVID-19 fight

Artificial intelligence has been introduced in the fight against COVID-19 and shows promise in identifying the level of infection suffered by patients.

A Princeton study authored by Jason Fleischer, a professor of electrical engineering, and graduated student Mohammad Tariqui uses an AI machine to show two basic types of lung damage a patient has suffered to find patterns, according to Princeton University News. 

One cancer shows a familiar form of pneumonia with restricted breathing and prevents oxygen to the bloodstream. Treatment often involves incubation. 

While the other shows low blood oxygen levels but the lungs work well, breathing is nearly normal and a sleep apnea machine can suffice for treatment. 

Hospitals have leaned on costly CT Scans, which aren't timely and not always accessible in rural areas, according to Princeton University. Fleischer’s machine can look at a X-ray and see patterns that aren't easily recognizable to the professionally-trained eye. It can also help doctors make sense of data that is difficult to interpret. 

The study hasn't been peer reviewed and Fleischer acknowledges the machine is another big piece to the puzzle. 

“Importantly, there is no change in practice,” Fleischer told Princeton University. “The technician doesn’t have to do anything differently. Hospitals don’t have to do any new procedure. With the X-rays they already have — and routinely take — we can give them this extra information.”