An algorithm based on artificial intelligence (AI) has been developed by researchers to identify atrial fibrillation, or irregular heart rhythm, in individuals who do not exhibit symptoms.
An irregular and frequently extremely fast heart rhythm known as atrial fibrillation (arrhythmia) can cause blood clots within the heart. It raises the risk of heart failure, stroke, and other heart-related issues.
The algorithm, which found hidden signals in common medical diagnostic tests, may help doctors better prevent strokes and other cardiovascular complications in patients with the most common type of heart rhythm disorder, according to the Smidt Heart Institute team at Cedars-Sinai Medical Center.
According to experts, around one in three patients with atrial fibrillation are unaware that they have the disorder.
The electrical impulses in the heart that control the flow of blood from the upper chambers to the lower chambers are disorganized in atrial fibrillation.
An ischemic stroke may result from blood pooling in the upper chambers and forming blood clots that go to the brain. Researchers used an artificial intelligence tool to analyse trends in ECG data in order to construct the algorithm.
A test that tracks the electrical impulses coming from the heart is called an electrocardiogram. Electrodes that measure cardiac electrical activity are placed to test patients’ bodies.
The software was trained to analyze ECG data gathered from January 1, 1987, to December 31, 2022. After studying over a million ECGs, the system correctly predicted that patients will get atrial fibrillation in less than 31 days.