A new study from the Smidt Heart Institute, in collaboration with Cedars-Sinai colleagues, introduces a new artificial intelligence (AI) program capable of detecting atrial fibrillation, a commonly undiagnosed abnormal heart rhythm.
Published in npj Digital Medicine, the study highlights the potential of AI to revolutionize the way doctors use echocardiograms—a test that employs sound waves to create images of the heart.
Atrial fibrillation is tricky because it can occur sporadically; it might not be active during a doctor’s appointment, making it hard to diagnose with traditional methods.
This condition can cause symptoms like heart palpitations, fatigue, and dizziness, or it might present no symptoms at all. However, if left unchecked, it can lead to severe consequences such as stroke and heart failure.
Neal Yuan, MD, a staff scientist with the Smidt Heart Institute and lead author of the study, explains, “Our AI algorithm can identify atrial fibrillation in patients during echocardiogram tests, even when the condition isn’t actively occurring.”
This ability to detect ‘hidden’ atrial fibrillation could be crucial for early intervention.
The AI program was trained using over 100,000 echocardiogram videos, enabling it to distinguish between normal heart rhythms and those indicative of atrial fibrillation.
Remarkably, it can predict which patients might develop or have had atrial fibrillation within the following 90 days, surpassing traditional risk assessment methods.
David Ouyang, MD, a cardiologist at the Smidt Heart Institute and one of the senior authors, noted the AI’s advantage, stating, “This technology could identify a dangerous condition that might be missed by the human eye when reviewing echocardiograms.”
This tool could be particularly beneficial for patients at risk of atrial fibrillation or those who exhibit related symptoms.
Christine M. Albert, MD, MPH, chair of the Department of Cardiology, emphasized the broader implications: “Identifying patients with hidden atrial fibrillation allows for earlier treatment, potentially averting serious cardiovascular events.”
This innovation offers a promising advance in cardiac care, leveraging AI to enhance diagnostic accuracy and patient outcomes in dealing with atrial fibrillation.
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The research findings can be found in npj Digital Medicine.
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