Alexander Van Esbroeck

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In this paper, we explore the application of motif discovery (i.e., the discovery of short characteristic patterns in a time series) to the clinical challenge of predicting intensive care unit (ICU) mortality. As part of the Physionet/CinC 2012 challenge, we present an approach that identifies and integrates information in motifs that are statistically(More)
Sleep analysis is critical for the diagnosis, treatment, and understanding of sleep disorders. However, the current standards for sleep analysis are widely considered oversimplified and problematic. The ability to automatically annotate different states during a night of sleep in a manner that is more descriptive than current standards, as well as the(More)
Recent work on heart rate motifs (HRM) has demonstrated that information in short heart rate patterns may be useful in identifying patients at elevated risk of cardiovascular death (CVD) following acute coronary syndrome. The information in HRM complements a variety of other clinical metrics including electrocardiographic (ECG) measures. While the HRM(More)
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