Researchers have made significant progress in developing an AI-based model that accurately predicts the onset of cardiac arrhythmia, specifically atrial fibrillation, about 30 minutes in advance. This innovative model, named WARN (Warning of Atrial fibRillatioN), utilizes deep-learning algorithms to analyze heart rate data and identify different phases, including normal sinus rhythm, pre-atrial fibrillation, and atrial fibrillation. By calculating a ‘probability of danger,’ WARN can provide early warnings when the probability crosses a specific threshold, signaling the impending onset of atrial fibrillation. The model’s low computational cost makes it suitable for integration into wearable technologies such as smartwatches, enabling real-time monitoring and early warnings for patients. This breakthrough has the potential to revolutionize heart health management, empowering patients to take proactive measures to maintain stable cardiac rhythm and mitigate the risks associated with irregular heartbeat.
AI-Powered Model Predicts Irregular Heartbeat 30 Minutes in Advance
