London, SANA-A study published in Nature Medicine indicates that an AI algorithm outperforms human technicians in analyzing long-term ECG recordings, particularly in identifying severe arrhythmias.
The AI analysis resulted in 14 times fewer missed diagnoses of conditions like complete heart block, ventricular tachycardia, and atrial fibrillation, according to the study. While the AI model had a higher rate of false positives, the overall reduction in missed diagnoses suggests a significant improvement in detecting critical arrhythmias.
A study shows that AI is better than humans at analyzing long-term heart rhythm monitoring.
AI is better than humans at analysing long-term ECG recordings
The researchers found that analysis by the AI led to 14 times fewer missed diagnoses of severe arrhythmias (including complete heart block, ventricular tachycardia, and atrial fibrillation). Severe arrhythmias were missed in 0.3 percent of patients by the AI, compared with 4.4 percent for the technicians.
The researchers’ intention was not to prove that AI is as good as or better than cardiologists for the diagnosis of specific arrhythmias. Rather, the study sought to determine what would happen if the technicians were replaced, and physicians received reports directly from the AI. If successful, such an approach would be a major innovation that could address the worldwide shortage of trained staff capable of interpreting long-term ECG monitoring.
“There is a shortage of around 15 million health workers worldwide. Ambulatory ECGs need to be analysed by specially trained staff, often called ECG technicians. Lack of staff leads to a huge bottleneck in healthcare worldwide, and at the same time, patients would benefit if we did more and longer ambulatory ECG recordings, not shorter. We believed that AI could solve this problem. That’s why we wanted to study what happens if you skip the ECG technicians altogether and let an AI algorithm do the job of detecting the arrhythmias, that cardiologists then review” says Johnson.
This is the first study to test not only how good the AI algorithm is at assessing individual selected ECG strips, but also what we could expect to happen if human technicians were replaced by AI.
Source: Nature Medicine
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