FDA Clears AI Tool That Spots Heart Failure Risks in Routine ECGs

Bunkerhill Health has secured FDA clearance for ECG-EF, an AI-powered tool that detects heart failure risks from standard ECGs. The technology measures ejection fraction—a critical indicator—directly from routine 12-lead electrocardiograms. This advancement aims to help clinicians identify high-risk patients sooner and with greater ease.

The ECG-EF algorithm analyses routine ECGs to spot reduced left ventricular ejection fraction (LVEF), a key marker of heart failure. Until now, measuring ejection fraction required additional imaging, which could delay diagnosis. With this AI solution, the process becomes faster, more accessible, and scalable for everyday clinical use.

Bunkerhill's ECG-EF is integrated into its Carebricks platform, which automates workflows across medical specialties. The system is designed to support clinical teams without adding to their workload, using generative AI to streamline decision-making. Carebricks already handles end-to-end processes, from data collection to actionable insights. Dr. Jag Singh, a cardiologist at Mass General Hospital, has praised the tool as a significant step forward in early heart failure detection. Studies supporting the technology include research from Imperial College London and Yale University, though widespread clinical adoption outside these trials remains limited. The company's focus is on making the tool available within existing healthcare systems, starting with its own platform.

The FDA clearance allows ECG-EF to be used in clinical settings, potentially improving outcomes by catching heart failure risks earlier. Clinicians can now access ejection fraction data from standard ECGs, reducing reliance on specialised imaging. For further details, Bunkerhill Health's media contact, Sean Bennett, can be reached at [email protected].