Researchers from the Smidt Heart Institute at Cedars-Sinai have developed an artificial intelligence (AI) algorithm capable of identifying abnormal heart rhythms in individuals without symptoms.
This breakthrough discovery could significantly enhance the prevention of strokes and other cardiovascular complications in patients with atrial fibrillation, the most common type of heart rhythm disorder.
Unlike previous algorithms primarily designed for specific populations, this AI model functions effectively across diverse patient groups and settings. The findings of this study were published in JAMA Cardiology.
Uncovering Hidden Heart Conditions:
It is estimated that approximately one in three individuals with atrial fibrillation remains undiagnosed, highlighting the need for improved detection methods.
Atrial fibrillation disrupts the heart’s electrical signals, causing chaotic rhythms that can lead to blood pooling in the heart’s upper chambers, forming clots that may trigger ischemic strokes.
AI Algorithm Development
To create this groundbreaking algorithm, researchers programmed an artificial intelligence tool to analyze patterns found in electrocardiogram (ECG) readings.
An ECG diagnostic test monitors the heart’s electrical activity by placing electrodes on the patient’s body.
The AI program was trained using nearly a million ECG readings from patients at two Veterans Affairs health networks collected between January 1, 1987, and December 31, 2022.
The algorithm successfully predicted the likelihood of atrial fibrillation within 31 days in these patients.
Additionally, the AI model was applied to medical records from Cedars-Sinai patients and demonstrated similar accurate predictions of atrial fibrillation within the same timeframe.
Wide Applicability
What makes this AI algorithm particularly promising is its applicability to diverse patient populations.
The study involving veterans showcased geographical and ethnic diversity, indicating that this algorithm could benefit the broader U.S. population.
This research exemplifies how AI is being leveraged to advance the preemptive management of complex cardiac conditions.
Future Directions
The investigators plan to continue their research by conducting prospective clinical trials to evaluate the algorithm’s ability to identify individuals at risk of heart attacks and strokes.
They also intend to develop additional AI algorithms to enhance cardiovascular care further.
In conclusion, developing an AI algorithm capable of detecting hidden heart conditions represents a significant stride toward proactive cardiovascular disease management.
This technology can potentially improve the early detection and prevention of atrial fibrillation-related complications, ultimately saving lives and enhancing patient care.
If you care about heart health, please read studies that vitamin K helps cut heart disease risk by a third, and a year of exercise reversed worrisome heart failure.
For more information about heart health, please see recent studies about supplements that could help prevent heart disease, stroke, and results showing this food ingredient may strongly increase heart disease death risk.
The research findings can be found in JAMA Cardiology.
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