Atrial fibrillation is the most common cardiac arrhythmia worldwide with around 59 million people concerned in 2019 . This irregular heartbeat is associated with increased risks of heart failure, dementia and stroke. It constitutes a significant burden to healthcare systems, making its early detection and treatment a major goal. Researchers from the Luxembourg Centre for Systems Biomedicine (LCSB) of the University of Luxembourg have recently developed a deep-learning model capable of predicting the transition from a normal cardiac rhythm to atrial fibrillation. It gives early warnings on average 30 minutes before onset, with an accuracy of around 80%. ...
Predicting arrhythmia 30 minutes before it happens
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