AI model detects heart failure signs via standard ECG

An international research study led by Italian institutions has developed an artificial intelligence model capable of detecting signs of heart failure through a standard electrocardiogram (ECG). The AI can identify micro-electrical signals invisible to the human eye that indicate high levels of NT-proBNP, a key biomarker for diagnosing heart failure.

Published in the ‘European Heart Journal – Quality of Care and Clinical Outcomes’, the study utilized a deep neural network trained on 84,895 ECGs and NT-proBNP tests. In clinical testing involving 679 patients in Cosenza and Trieste, the algorithm demonstrated nearly 90% accuracy in identifying at-risk values. This technology could potentially offer a faster, cheaper alternative to blood tests and echocardiograms.

The collaborative research involved several institutions, including the University of Calabria, Humanitas University, University of Naples Federico II, University of Trieste, University of Zurich, Imperial College London, King’s College London, and Seoul National University.