Predicting cardiac arrhythmia 30 minutes before it happens.

Researchers from the Luxembourg Centre for Systems Biomedicine have developed a deep-learning model called WARN (Warning of Atrial fibRillatioN) that can predict the transition from a normal cardiac rhythm to atrial fibrillation. Atrial fibrillation is the most common cardiac arrhythmia worldwide and is associated with increased risks of heart failure, dementia, and stroke. The model gives early warnings of atrial fibrillation on average 30 minutes before onset, with an accuracy of around 80%. This development could pave the way for integration into wearable technologies, allowing for early interventions and better patient outcomes. [Extracted from the article]