<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-21T12:11:08Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/61574" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/61574</identifier><datestamp>2022-01-13T07:54:29Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Collin M. Stultz.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Sarker, Joyatee Mudra</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2011-03-07T15:17:23Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2011-03-07T15:17:23Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2010</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2010</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/61574</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">703280207</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (p. 65-68).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Patients who have had an acute coronary syndrome (ACS) are at a relatively high risk of having subsequent adverse cardiac events. Several electrocardiographic (ECG) measures such as heart rate variability, heart rate turbulence, deceleration capacity, T-wave altemans, and morphologic variability have been used to identify patients at an increased risk of recurrent myocardial infarctions and cardiovascular death. In this work, we develop a new ECG-based measure for patient risk stratification called weighted morphologic variability. This measure is based on assessment of beat-to-beat changes in the morphology of consecutive beats. Weighted morphologic variability identifies patients who are at more than four-fold risk for cardiovascular death, which is an improvement in ECG-based risk stratification. The body of this work suggests that prognosticating patients based on electrocardiographic measures is an effective way of identifying those at risk of adverse cardiovascular outcomes.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Joyatee Mudra Sarker.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">M.Eng.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">68 p.</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">M.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.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Association of adverse cardiovascular outcomes with weighted morphologic variability following non-ST-elevation acute coronary syndromes</dim:field>
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   	&lt;Title>Association of adverse cardiovascular outcomes with weighted morphologic variability following non-ST-elevation acute coronary syndromes&lt;/Title>
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   	&lt;PublicationDate>2010&lt;/PublicationDate>
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        	&lt;DisplayName>Sarker, Joyatee Mudra&lt;/DisplayName>
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            &lt;DisplayName>Massachusetts Institute of Technology&lt;/DisplayName>
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    &lt;Keyword>Electrical Engineering and Computer Science.&lt;/Keyword>
   	&lt;Abstract>Patients who have had an acute coronary syndrome (ACS) are at a relatively high risk of having subsequent adverse cardiac events. Several electrocardiographic (ECG) measures such as heart rate variability, heart rate turbulence, deceleration capacity, T-wave altemans, and morphologic variability have been used to identify patients at an increased risk of recurrent myocardial infarctions and cardiovascular death. In this work, we develop a new ECG-based measure for patient risk stratification called weighted morphologic variability. This measure is based on assessment of beat-to-beat changes in the morphology of consecutive beats. Weighted morphologic variability identifies patients who are at more than four-fold risk for cardiovascular death, which is an improvement in ECG-based risk stratification. The body of this work suggests that prognosticating patients based on electrocardiographic measures is an effective way of identifying those at risk of adverse cardiovascular outcomes.&lt;/Abstract>
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