A team of medical researchers has unveiled an artificial intelligence system capable of detecting heart disease indicators from standard electrocardiogram readings in less than two seconds. The technology was trained using data from millions of patients and processes electrical activity recordings from the heart to identify markers of disease that may not be immediately apparent to human observers.
The innovation addresses a significant gap in current diagnostic practice. While electrocardiograms have been used for over a century to assess heart rate and rhythm, they cannot definitively detect heart disease. Patients suspected of having conditions such as heart failure or valve disease typically require an echocardiogram, an ultrasound-based scan for which waiting periods often extend several months. The new AI tool aims to streamline this process by flagging high-risk patients who can then be prioritized for more definitive imaging studies.
A clinical trial involving 67,000 patients in the United States demonstrated the system’s effectiveness, identifying up to 81 percent of heart failure cases and up to 90 percent of valve disease cases. Researchers presented findings at the European Society of Cardiology annual congress in Munich. The development carries particular significance given that approximately one billion electrocardiograms are performed globally each year, meaning the technology could potentially be applied across millions of patients.
Experts emphasize that while the AI tool cannot independently diagnose or rule out these conditions, it provides a strong indication of risk and could enable faster access to confirmatory testing. Early detection is critical for these conditions, as timely intervention with appropriate medications can prevent serious complications. Researchers also noted that the system could opportunistically identify at-risk patients undergoing ECGs for unrelated reasons, potentially catching previously undiagnosed disease.
Research teams are now working toward developing portable, handheld versions of the technology for use by healthcare professionals. In related developments, scientists presented research suggesting that artificial intelligence analysis of brief facial videos may also aid in detecting undiagnosed high blood pressure and type 2 diabetes.
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