AI trained on heartbeats
New studies show AI can spot abnormal heart rhythms within a matter of seconds.
A ten-second, non-invasive test using artificial intelligence (AI) has been found to identify patients with atrial fibrillation – abnormal heart rhythm – even when their heart rhythm seems normal.
The study, which involved almost 181,000 patients, used AI to find signals in heart scans that might be invisible to the human eye, but are important to detect potential heart issues.
Atrial fibrillation is particularly difficult to diagnose because heartbeats can go in and out of rhythm, but the AI had an accuracy of 83 per cent.
“Applying an AI model to the ECG permits detection of atrial fibrillation even if not present at the time the ECG is recorded. It is like looking at the ocean now and being able to tell that there were big waves yesterday,” said Dr Paul Friedman, Chair of the Department of Cardiovascular Medicine at the Mayo Clinic, USA.
“Currently, the AI has been trained using ECGs in people who needed clinical investigations, but not people with unexplained stroke nor the overall population, and so we are not yet sure how it would perform at diagnosing these groups.
“However, the ability to test quickly and inexpensively with a non-invasive and widely available test might one day help identify undiagnosed atrial fibrillation and guide important treatment, preventing stroke and other serious illness.”
The AI performed well at identifying the presence of atrial fibrillation: testing on the first cardiac ECG output from each patient, the accuracy was 79 per cent (for a single scan), and when using multiple ECGs for the same patient the accuracy improved to 83 per cent.
Further research is needed to confirm the performance on specific populations, such as patients with unexplained stroke (embolic stroke of undetermined source - ESUS), or heart failure.