An international team of researchers have shown that artificial intelligence (AI) analysis of long-term electrocardiogram (ECG) recordings surpasses the current standard performed by human technicians, with 14 times fewer missed diagnosis.
Linda Johnson
These findings were presented in the Late Breaking Science session at the ESC Congress 2024 by PHRI Associate Investigator Linda Johnson, who led the study alongside PHRI Senior Scientist Jeff Healey.
The study evaluated DeepRhythmAI, a cloud-based software for assessing cardiac arrhythmias using two-lead ECG data, in 14,606 adult patients who recorded an average of 14 days of ECG data.
Researchers compared DeepRhythmAI to usual care, where licensed ECG technicians analyzed the same recordings. The AI demonstrated higher sensitivity in detecting critical arrhythmias—such as atrial fibrillation, heart block, and ventricular tachycardia—resulting in 14 times fewer missed events. Additionally, the AI achieved an accuracy of 99.9% in correctly identifying patients who did not have critical arrhythmias.
On the significance of this study, Jonson said “On the significance of this study, Johnson said, “Ambulatory ECG analysis by human technicians is time-consuming and challenging, leading to high costs and risk of error. At the same we know that long recording times are needed to find clinically relevant arrhythmias.”
“We hope that these results can be translated to more accurate diagnostics, better access to care, and improved patient outcomes.”
@lsjMD just presented our huge endeavor in the DRAI MARTINI (coolest name for a study ever). AI was superior to technician ECG-analysis with only a modest increase in the false positive rate! Stay tuned for the paper! #ESCCongress #ESCCongress2024 @StavrosStavrak1 @CTECresearch pic.twitter.com/5tiSlyXSUI
— Stefanos Zafeiropoulos, MD, MS, PhD (@Cardiaficionado) August 30, 2024
