dc.contributor.authorLiu, Nan
dc.contributor.authorLin, Zhiping
dc.contributor.authorCao, Jiuwen
dc.contributor.authorKoh, Zhixiong
dc.contributor.authorZhang, Tongtong
dc.contributor.authorHuang, Guang-Bin
dc.contributor.authorSer, Wee
dc.contributor.authorOng, Marcus Eng Hock
dc.date.accessioned2013-10-14T03:00:42Z
dc.date.available2013-10-14T03:00:42Z
dc.date.copyright2012en_US
dc.date.issued2012
dc.identifier.citationLiu, N., Lin, Z., Cao, J., Koh, Z., Zhang, T., Huang, G. B., et al. (2012). An intelligent scoring system and its application to cardiac arrest prediction. IEEE transactions on information technology in biomedicine, 16(6), 1324-1331.
dc.identifier.urihttp://hdl.handle.net/10220/16465
dc.description.abstractTraditional risk score prediction is based on vital signs and clinical assessment. In this paper, we present an intelligent scoring system for the prediction of cardiac arrest within 72 h. The patient population is represented by a set of feature vectors, from which risk scores are derived based on geometric distance calculation and support vector machine. Each feature vector is a combination of heart rate variability (HRV) parameters and vital signs. Performance evaluation is conducted on the leave-one-out cross-validation framework, and receiver operating characteristic, sensitivity, specificity, positive predictive value, and negative predictive value are reported. Experimental results reveal that the proposed scoring system not only achieves satisfactory performance on determining the risk of cardiac arrest within 72 h but also has the ability to generate continuous risk scores rather than a simple binary decision by a traditional classifier. Furthermore, the proposed scoring system works well for both balanced and imbalanced datasets, and the combination of HRV parameters and vital signs shows superiority in prediction to using HRV parameters only or vital signs only.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesIEEE transactions on information technology in biomedicineen_US
dc.subjectDRNTU::Science::Medicine::Biomedical engineering
dc.titleAn intelligent scoring system and its application to cardiac arrest predictionen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1109/TITB.2012.2212448


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