AI spots signs of heart disease in routine ECGs within seconds
Researchers at Imperial College London have developed an AI model capable of identifying heart disease markers in routine ECGs within seconds. The tool is currently undergoing NHS testing to determine its clinical viability for future patient care.
Why it matters
This technology could significantly improve early detection rates for heart failure and valve disease, potentially saving lives through more efficient diagnostic workflows.
Imperial researchers report AI can flag signs of heart disease in routine ECGs within seconds. NHS testing will assess its value for clinical follow-up.
Imperial College London researchers have developed an AI model that reportedly reads a routine electrocardiogram, or ECG, in under two seconds and flags signs of reduced heart pumping function and aortic valve disease. The prospect is an additional way to identify patients who need further investigation from a test clinicians already collect.
As covered in The Rundown’s September 1 newsletter , the researchers were preparing to test the approach in NHS care. The Guardian reported on August 31 that the tool detected the targeted conditions in up to 81% and 90% of cases. Subsequent reporting adds important detail to those headline figures.
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