
Deep Learning Measures Heart Intervals More Accurately
Standard automated ECG software often misses critical cardiac warning signs, but a new deep learning model trained on UK Biobank data proves we can do much better.
Discover the newest research about AI innovations in 🫀 Cardiology.

Standard automated ECG software often misses critical cardiac warning signs, but a new deep learning model trained on UK Biobank data proves we can do much better.

The sudden collapse of a major heart failure trial exposes a quiet failure point in how regulators fast-track medical technology.

A new deep learning model can locate dangerous heart arrhythmia targets without needing to trigger the life-threatening rhythm first.

A new machine learning model can help hospitals predict which heart surgery patients will get stuck in the ICU, but its performance drop in external testing highlights a persistent hurdle for clinical AI.

A delayed regulatory nod puts Boston Scientific’s multi-billion-dollar bet to the test.

A new open-source AI model successfully automates the tedious manual tracking of heart chambers and blood flow velocity, moving cardiac imaging past simple ventricular checks.

A new wave of AI models is finding invisible patterns in routine heart tests to predict sudden cardiac arrest before it strikes.

A new machine learning model proves that tracking silent organ damage is far more predictive of survival than standard blood pressure readings.

A routine test that costs pennies can now spot hidden heart failures before symptoms even appear.

An overlooked hormonal condition drives millions of hypertension cases, but a new algorithmic approach could finally bring it into the light.