AI ECG Tool Flags Heart Risk in Two Seconds, but Still Needs the Scan That Diagnoses It
The reported results suggest routine electrical heart traces could help prioritize scarce ultrasound appointments. The system’s stated role, however, stops short of confirming disease or ruling it out.
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3 key pointsResearchers led through Imperial College London presented an AI ECG system that scans routine heart traces in under two seconds and flags patients who may need urgent follow-up. In a 67,000-patient US trial, it identified up to 81% of heart-failure cases and 90% of valve-disease cases, but those figures are case-finding results—not diagnoses. The clinical opportunity is triage: prioritizing echocardiograms, which remain necessary and can involve months-long waits.
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The system was trained on millions of routine ECGs to detect signals not typically visible in recordings.
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Echocardiography remains the required confirmation test; the AI cannot diagnose or rule out either condition.
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Researchers propose deploying it across hospital ECGs to surface previously unsuspected disease.
A newly presented AI ECG system can produce a risk read-out from a routine heart trace in less than two seconds. It may help move people with possible heart failure or valve disease toward faster ultrasound scans, but it cannot diagnose or exclude either condition by itself.
The findings were presented at the European Society of Cardiology annual congress in Munich. The British Heart Foundation funded the research, which was led through an Imperial College London analysis. Researchers trained the model on millions of routine ECGs to extract signals beyond those typically visible in the recordings.
Case finding is not a clinical verdict
In a US trial of 67,000 patients, the tool identified up to 81% of patients with heart failure and up to 90% of those with heart valve disease. Those results describe how many cases the tool identified in that trial; they do not make its output a definitive diagnosis.
The trial included 67,000 patients in the US.
The valve-disease result came from the same trial.
The proposed gain is speed to echocardiography
An ECG records the heart’s electrical activity, including its rate and rhythm. Diagnosis of heart failure or valve disease requires an echocardiogram, an ultrasound scan of the heart, and patients can wait several months after referral for that scan.
That makes the tool a routing layer rather than a replacement for clinical assessment. Researchers said it could identify the patients at greatest risk so they can be prioritized for faster, more urgent echocardiograms. They also proposed running it across hospital ECGs to flag people whose conditions were not previously suspected.
The next hardware question
Ahmed El-Medany, the British Heart Foundation clinical research fellow who led the Imperial analysis, said the next challenge is designing handheld AI-led ECG readers for healthcare professionals. For now, the evidence supports a fast risk flag followed by confirmatory scanning, rather than a standalone diagnostic device.
Sources
- theguardian.com‘Superhuman’ AI tool spots heart disease in less than 2 seconds
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