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BACKGROUND AND AIM Rapid and sensitive detection of atrial fibrillation (AF) is of paramount importance for initiation of adequate preventive therapy after stroke. Stroke Unit care includes continuous electrocardiogram monitoring (CEM) but the optimal exploitation of the recorded ECG traces is controversial. In this retrospective single-center study, we investigated whether an automated analysis of continuous electrocardiogram monitoring (ACEM), based on a software algorithm, accelerates the detection of AF in patients admitted to our St

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