AI rapidly assesses ECGs for patient prioritization
Researchers from Imperial College London have developed an artificial intelligence-based tool capable of analyzing electrocardiograms (ECGs) in under two seconds. The goal is to assist doctors in identifying patients who require more detailed cardiac examinations, such as ultrasound imaging. The tool utilizes training models based on millions of data points to detect precise patterns indicating heart failure and valve diseases, with accuracy rates of up to 81% and 90%, respectively. It also improves patient triage based on risk levels. While these promising results are encouraging, the tool is not yet a definitive diagnostic. Instead, it acts as an aid in prioritizing patients, helping to reduce waiting times for those at greater risk. Future plans include integrating this technology into portable devices.
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