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dc.contributor.advisorJohn V. Guttag.en_US
dc.contributor.authorSung, Philip Pohongen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2010-03-24T20:35:47Z
dc.date.available2010-03-24T20:35:47Z
dc.date.copyright2009en_US
dc.date.issued2009en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/52769
dc.descriptionThesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionIncludes bibliographical references (p. 95-100).en_US
dc.description.abstractPatients who have suffered an acute coronary syndrome (ACS) are at elevated risk of future adverse events, including fatal arrhythmias or myocardial infarction. Risk stratification--he identification of high-risk patients--s an important step in determining who is most likely to benefit from aggressive treatments. We propose a new automated risk stratification technique that uses the long-term electrocardiographic data routinely recorded in the days following an ACS. Data obtained from clinical drug trials indicates that our technique, called MV-DF (morphologic variability diagnostic frequencies), can significantly improve prognostication for ACS patients. Patients with MV-DF values in the highest quartile show a more than five-fold elevated risk of death in the 90 days following a non-ST-elevation ACS. We also propose techniques to construct models of the dynamics of cardiac behavior. Preliminary results suggest that such techniques may be useful for short-term prediction of fatal arrhythmias. Our results suggest that long-term ECG-based risk assessment techniques--n particular, methods incorporating information about morphologic variability--re an effective and practical way to select appropriate treatment options for cardiovascular disease patients.en_US
dc.description.statementofresponsibilityby Philip Pohong Sung.en_US
dc.format.extent100 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleRisk stratification by analysis of electrocardiographic morphology following acute coronary syndromesen_US
dc.typeThesisen_US
dc.description.degreeM.Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.identifier.oclc505525431en_US


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