Groundbreaking study shows AI benefits in heart attack detection
A new study using artificial intelligence to analyze electrocardiograms, led in part by Benjamin Cooper, MD, MEd, associate professor in the Department of Emergency Medicine at McGovern Medical School at UTHealth Houston, showed significant improvement in the detection of severe heart attacks and the reduction of false positives.
The study, published by lead author Robert Herman, MD, PhD, cardiovascular researcher at AZORG Hospital in Aalst, Belgium, was recently presented at the Transcatheter Cardiovascular Therapeutics Symposium in San Francisco.
“Our research showed that an AI tool called Queen of Hearts by Powerful Medical was much better at spotting real heart attacks and avoiding false alarms compared to standard methods,” Cooper said.
The study focused on how AI can help doctors interpret electrocardiograms to quickly and accurately diagnose heart attacks, specifically ST-segment elevation myocardial infarction. ST-segment elevation myocardial infarction occurs when a major artery is blocked, preventing blood flow into the heart.
“AI-driven ECG interpretation can bring the best of both worlds — identify true heart attacks early while reducing unnecessary activations,” Herman said. “Improving the accuracy of triage at the first medical contact can streamline emergency care, reduce fatigue and strain on clinical teams, and ensure that patients who truly need urgent intervention receive it without delay.”
By analyzing more than 1,032 patients across three major hospitals, the Queen of Hearts AI improved sensitivity from 71% to 92% and cut false-positive activations from 41.8% to 7.9%. The technology also can be used via a smartphone or integrated into hospital systems, making it practical for emergency medicine departments, as well as ambulances.
“These results indicate that AI-enhanced STEMI diagnosis at the first medical contact has the potential to shorten time to treatment and reduce false activations,” said Timothy D. Henry, MD, FACC, senior author of the study and medical director of the Carl and Edyth Lindner Center for Research at The Christ Hospital in Cincinnati. “This technology may be especially valuable in optimizing the transfer of STEMI patients from non-PCI centers to ensure timely and appropriate care.”
Cooper contributed to patient data collection and clinical interpretation at Memorial Hermann–Texas Medical Center to ensure that the study reflected real-world emergency care practices. The overall study was published in “JACC: Cardiovascular,” while the findings from Memorial Hermann will be published in the “European Heart Journal: Digital Health.”
“This research is a game-changer for emergency cardiology,” Cooper said. “By using AI to interpret ECGs, we can identify heart attacks faster and more accurately, even in cases that don’t look typical. That means fewer unnecessary procedures, better use of resources, and — most importantly — quicker treatment for patients who truly need it.”
Moving forward, researchers will begin prospective trials to confirm the impact of Queen of Hearts on patient outcomes and workflow efficiency. The team at Memorial Hermann is planning a six-month pilot program through the Memorial Hermann Innovation Hub.