An article published in the Lancet looked at diagnosing AF which is is frequently asymptomatic and thus underdetected but is associated with stroke, heart failure, and death. Existing screening methods require prolonged monitoring and are limited by cost and low yield. They looked at whether a rapid, inexpensive, point-of-care means of identifying these patients with atrial fibrillation using machine learning could be developed.
Researchers said it was still early days, but believe the system could lead to earlier and easier detection of the problem and, therefore, ensure patients get the right treatment, saving lives. This abstract is available at The Lancet and was featured on the bbc website here.