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A decision support system for reducing false alarms in ICU
Keywords Machine learning, Biomedical signal processing, Clinical decision support, Temporal data analysis  +
Level Master  +
OneLineSummary Developing a clinical decision support system using machine learning and biomedical signal analysis techniques for an ICU setting.  +
Prerequisites Good knowledge of applied mathematics and signal processing. An ability to implement state-of-the-art algorithms in a suitable programming environment. An interest in machine learning algorithms.  +
References 1. Liu C, Zhao L, Tang H, Li Q, Wei S, Li 1. Liu C, Zhao L, Tang H, Li Q, Wei S, Li J. Life-threatening false alarm rejection in ICU: using the rule-based and multi-channel information fusion method. Physiological Measurement. 2016;37(8):1298. 2. Konkani A, Oakley B, Bauld TJ. Reducing hospital noise: a review of medical device alarm management. Biomedical Instrumentation & Technology. 2012;46(6):478-87. 3. Cvach M. Monitor alarm fatigue: an integrative review. Biomedical Instrumentation & Technology. 2012;46(4):268-77. 4. Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PC, Mark RG, et al. PhysioBank, PhysioToolkit, and PhysioNet. Circulation. 2000;101(23):e215.PhysioNet. Circulation. 2000;101(23):e215.
StudentProjectStatus Internal Draft  +
Supervisors Sławomir Nowaczyk + , Awais Ashfaq +
TimeFrame Winter 2016 / Spring 2017  +
Title A decision support system for reducing false alarms in ICU  +
Categories StudentProject  +
Modification dateThis property is a special property in this wiki. 4 October 2017 18:51:37  +
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