Reduction of false cardiac arrhythmia alarms through the use of machine learning techniques

Abstract

Due to the so-called “crying wolf” effect, frequent false cardiac arrhythmia alarms have been shown to diminish staff attentiveness and thus reduce the quality of care patients receive in the ICU. The PhysioNet/Computing in Cardiology 2015 Challenge seeks to improve patient care by decreasing the number of these false cardiac arrhythmia alarms… (More)

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Cite this paper

@article{Caballero2015ReductionOF, title={Reduction of false cardiac arrhythmia alarms through the use of machine learning techniques}, author={Miguel Angel Araque Caballero and Grace M. Mirsky}, journal={2015 Computing in Cardiology Conference (CinC)}, year={2015}, pages={1169-1172} }