Researchers led by the University of Cambridge analyzed heart sounds from nearly 1,800 patients using an AI algorithm trained to recognize valve disease, a condition that often goes undiagnosed until it becomes life-threatening.
The AI correctly identified 98% of patients with severe aortic stenosis, the most common form of valve disease requiring surgery, and 94% of those with severe mitral regurgitation, where the heart valve doesn't fully close and blood leaks backward across the valve.
The technology, which works with digital stethoscopes, outperformed GPs at detecting valve disease, and could be used as a rapid screening tool in primary care.
The results are reported in the journal npj Cardiovascular Health.
Rather than training the algorithm to recognize heart murmurs - the traditional diagnostic marker - the researchers trained it directly on echocardiogram results.
This allowed the system to learn subtle acoustic patterns that humans might miss, including cases with no obvious murmur.
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