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Identification of patients at risk to develop atrial fibrillation (AF) can enable more frequent follow-up and lead to earlier detection of AF. The aim of this project was to perform long-term AF prediction based on a novel set of ECG-derived features describing the characteristics of supraventricular arrhythmias present before new onset AF. In total, 12 199 patients aged 75/76 performed repeated s
