In a new study, researchers found that artificial intelligence (AI) can detect the signs of irregular heart rhythm, atrial fibrillation (AF), in an EKG accurately.
The detection is effective even if the heart is in normal rhythm at the time of a test.
The research was conducted by a team from Mayo Clinic.
While common, atrial fibrillation often is fleeting and hard to diagnose.
Atrial fibrillation may not occur during a standard 10-second, 12-lead EKG, and people are often unaware of its presence.
Prolonged monitoring methods, such as a loop recorder, require a procedure and are expensive.
But accuracy and timeliness are important in making an atrial fibrillation diagnosis.
If left undetected, atrial fibrillation can cause stroke, heart failure, and other heart diseases.
Knowing that a patient has atrial fibrillation helps direct treatment with blood thinners. Blood thinners are very effective for preventing another stroke in people with AF.
But for those without AF, using blood thinners increases the risk of bleeding without substantial benefit.
In the new study, the team used about 450,000 EKGs of the over 7 million EKGs in the Mayo Clinic digital data vault.
They trained AI to identify subtle differences in a normal EKG that would indicate changes in heart structure caused by atrial fibrillation.
These changes are not detectable without the use of AI.
The researchers then tested the 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% accuracy.
The team says 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.
It will a noninvasive and widely available method of heart disease screening.
One author of the study is Paul Friedman, M.D., chair of the Department of Cardiovascular Medicine at Mayo Clinic.
The study is published in The Lancet.
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