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dc.contributor.authorAhmed, Tarem
dc.contributor.authorAhmed, Supriyo Shafkat
dc.contributor.authorChowdhury, Fazle Elahi
dc.identifier.citationAhmed, T., Ahmed, S., & Chowdhury, F. E. (2016). Taking meredith out of grey's anatomy: Automating hospital ICU emergency signaling. Paper presented at the ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, , 2016-May 1886-1890. doi:10.1109/ICASSP.2016.7472004en_US
dc.descriptionThis conference paper was presented in the 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 [© 2016 Institute of Electrical and Electronics Engineers Inc.] The conference paper's definite version is available at: http:// 10.1109/ICASSP.2016.7472004en_US
dc.descriptionThis is a scopus indexed conference paper.
dc.description.abstractIn this paper we propose a new algorithm based on kernel machines for automatic, instantaneous detection of emergencies occurring in a hospital Intensive Care Unit. The proposed algorithm takes as input the multitude of vital statistics that are continuously monitored for a critical patient in Intensive Care, learns the underlying pattern between the statistics that is naturally inherent for the particular patient, and instantaneously signals any deviation from this pattern. Through application to real data from a cardiac Intensive Care Unit at a hospital in a developing country, we show that it is possible to easily obtain high detection accuracy with low false alarm rates.en_US
dc.publisher© 2016 Institute of Electrical and Electronics Engineers Inc.en_US
dc.subjectICU emergency signalingen_US
dc.subjectSignal processingen_US
dc.titleTaking meredith out of Grey's anatomy: automating hospital ICU emergency signalingen_US
dc.typeConference paperen_US
dc.contributor.departmentDepartment of Electrical and Electronic Engineering, BRAC University

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