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Predicting cardiac arrhythmia 30 minutes before it happens - EurekAlert
<p><strong>Atrial fibrillation is the most common cardiac arrhythmia worldwide with around </strong><strong>59 million people concerned in 2019</strong><strong>. 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 </strong><strong>Luxembourg Centre for Systems Biomedicine</strong><strong> (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%. These results, </strong><strong>published in the scientific journal <em>Patterns</em></strong><strong>, pave the way for integration into wearable technologies, allowing early interventions and better patient outcomes.</strong></p>
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