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dc.contributor.advisorRoger G. Mark.en_US
dc.contributor.authorGreenwald, Scott Daviden_US
dc.contributor.otherHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.date.accessioned2005-10-07T20:45:22Z
dc.date.available2005-10-07T20:45:22Z
dc.date.copyright1990en_US
dc.date.issued1990en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/29206
dc.descriptionThesis (Ph. D.)--Harvard University--Massachusetts Institute of Technology Division of Health Sciences and Technology, Program in Medical Engineering and Medical Physics, 1990.en_US
dc.descriptionIncludes bibliographical references (p. 242-247).en_US
dc.description.statementofresponsibilityby Scott David Greenwald.en_US
dc.format.extent247 p.en_US
dc.format.extent17847418 bytes
dc.format.extent17847174 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
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/1721.1/7582
dc.subjectHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.titleImproved detection and classification of arrhythmias in noise-corrupted electrocardiograms using contextual informationen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.identifier.oclc24206532en_US


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