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Study: AI Detects Heart Failure via ECG in Under 2 Seconds

The system identified up to 81% of heart failure cases and 90% of valve disease cases from ECGs, researchers said.

  • On Monday, Imperial College London researchers presented an AI system at the European Society congress in Munich that reads ECGs in under two seconds to identify heart conditions clinicians often miss.
  • Designed to address clinical capacity problems, researchers trained models on 1.6 million ECGs from The Brazilian dataset linked to patient records, enabling the system to learn predictive patterns.
  • A trial covered 67,000 patients in the United States, with the team reporting 83% to 93% accuracy for heart disease and 70% to 80% accuracy for other conditions.
  • The BHF-funded work is being commercialized through a spinout called Cardiovolt, with Professor Siong serving as chief medical officer; the AI is designed for triage rather than replacing clinicians.
  • Moving from academic results to routine hospital use requires clinical validation and regulatory approval; the technology could eventually expand to Handheld ECG devices, identifying conditions including diabetes and kidney disease.
Insights by Ground AI

36 Articles

Right

An innovation developed by Imperial College in London uses artificial intelligence to interpret electrocardiograms (ECG) in less than two seconds. The system effectively identifies the risks of heart failure and valve diseases, providing doctors with an ultra-fast diagnostic tool.

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Lean Right

Heart failure is a common problem. A British team of researchers is training an AI with millions of heart curves. Up to 90 percent of the patients at risk should be able to detect the software using an ECG.

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Cardiovascular News broke the news on Tuesday, August 25, 2026.
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