The AI-enabled EKG can detect recent atrial fibrillation that occurred without symptoms or that is impending, potentially improving treatment options.
The research could improve the efficiency of the EKG, a noninvasive and widely available method of heart disease screening, said the study published in The Lancet.
While common, atrial fibrillation often is fleeting and is challenging to diagnose.
"When people come in with a stroke, we really want to know if they had atrial fibrillation in the days before the stroke, because it guides the treatment," said Paul Friedman, Chair of the Department of Cardiovascular Medicine at Mayo Clinic.
Blood thinners are very effective for preventing another stroke in people with atrial fibrillation.
"For those without atrial fibrillation, using blood thinners increases the risk of bleeding without substantial benefit. That's important knowledge. We want to know if a patient has AF," said Friedman.
Researchers tested AI on normal-rhythm EKGs from a group of 36,280 patients, of whom 3,051 were known to have atrial fibrillation. The AI-enabled EKG correctly identified the subtle patterns of atrial fibrillation with 90 per cent accuracy.
If proven out, AI-guided EKGs could direct the right treatment for disease caused by atrial fibrillation, even without symptoms.
Moreover, this technology can be processed using a smartphone or watch, making it readily available on a large scale.
( With inputs from IANS )