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dc.contributor.authorSingh, Anima
dc.contributor.authorLiu, J.
dc.contributor.authorGuttag, John V.
dc.date.accessioned2012-07-30T20:12:40Z
dc.date.available2012-07-30T20:12:40Z
dc.date.issued2011-03
dc.date.submitted2010-09
dc.identifier.isbn978-1-4244-7319-9
dc.identifier.isbn978-1-4244-7318-2
dc.identifier.issn0276-6547
dc.identifier.urihttp://hdl.handle.net/1721.1/71901
dc.description.abstractWe investigate several entropy based approaches to finding cut points for discretizing continuous ECG-based risk metrics. We describe two existing approaches, Shannon entropy and asymmetric entropy, and one new approach, warped entropy. The approaches are used to find cut points for the end point of cardiovascular death for three risk metrics: heart rate variability (HRV LF-HF), morphological variability (MV) and deceleration capacity (DC). When trained on multiple instances of training set containing 2813 patients, warped entropy yielded the most robust cut-offs. The performance of the cutoffs obtained using warped entropy from the training sets was compared with those in the literature using a Naive Bayes classifier on corresponding test sets. Each test set contained 1406 patients. The resulting classifier resulted in a significantly (p<;0.05) improved recall rate at the expense of a lower precision.en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5738012en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceIEEEen_US
dc.titleDiscretization of continuous ECG based risk metrics using asymmetric and warped entropy measuresen_US
dc.typeArticleen_US
dc.identifier.citationSingh A. et al., "Discretization of continuous ECG based risk metrics using asymmetric and warped entropy measures." IEEE, 2010. 473 - 476. © Copyright 2010 IEEEen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.approverGuttag, John V.
dc.contributor.mitauthorSingh, Anima
dc.contributor.mitauthorLiu, J.
dc.contributor.mitauthorGuttag, John V.
dc.relation.journal2010 Computing in Cardiologyen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
dc.identifier.orcidhttps://orcid.org/0000-0003-0992-0906
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


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