AI tool detects heart disease from ECG in under two seconds

Doctors have unveiled an artificial‑intelligence system that can detect heart disease from a standard electrocardiogram (ECG) in under two seconds. Trained on data from millions of routine ECGs, the algorithm extracts subtle patterns and signals that are typically invisible to the human eye, allowing it to flag abnormalities with a “superhuman” level of sensitivity. The tool was developed by a team of clinicians and data scientists who used a large, diverse dataset to teach the model how to recognize early signs of coronary artery disease, arrhythmias, and other cardiovascular conditions.

In clinical trials, the AI demonstrated a markedly higher detection rate than conventional ECG interpretation, identifying high‑risk patients who might otherwise have been missed by manual review. By providing instant risk stratification, the system enables clinicians to triage patients more efficiently, potentially accelerating referrals for invasive testing, medication adjustments, or surgical interventions. The technology also offers a scalable solution for busy practices and remote settings, where rapid, accurate assessment can improve patient outcomes and reduce the burden on specialized cardiac services.

If adopted widely, this AI‑powered ECG analysis could streamline the diagnostic pathway for cardiovascular disease, allowing high‑risk individuals to receive timely treatment and lowering the incidence of adverse events. The developers are now working with regulatory bodies to secure approval and plan larger, real‑world studies to confirm the system’s effectiveness across varied patient populations.