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dc.contributor.advisorMichael Stonebraker.en_US
dc.contributor.authorZhou, Erica,M. Eng.(Massachusetts Institute of Technology)en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.coverage.spatialn-us---en_US
dc.date.accessioned2021-01-06T18:31:10Z
dc.date.available2021-01-06T18:31:10Z
dc.date.copyright2020en_US
dc.date.issued2020en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/129142
dc.descriptionThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, September, 2020en_US
dc.descriptionCataloged from student-submitted PDF of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 71-73).en_US
dc.description.abstractIn the medical setting, prevention of healthcare-acquired infections (HAIs) is an important area of research in order to mitigate extraneous complications and medical costs. In the United States alone, infections caused by the Clostridioides difficile (C. difi) bacteria affect up to 500,000 hospital patients annually and can have serious, even fatal, consequences. C. difi can spread person to person through direct contact as well as indirect contact through infected surfaces, equipment, or people. However, through current means, it is difficult to quantify exactly how infection is transmitted and, consequently, how to best manage and combat it. Using Kyrix, a pan-and-zoom data visualization platform, we propose an interactive visualization system to depict connections between hospital patients that may be used to identify possible routes of transmission such as shared hospital rooms, reusable medical equipment, and common providers. By taking advantage of the "zoom" functionality, users can access the data at various levels of specificity, starting with a 3D overview of the hospital, zooming into specific floors or rooms of interest, learning about individual patient cases, and finally honing in on a specific patient and their connections with other patients. With such a system, hospital epidemiologists can quickly and easily identify interactions that may represent opportunities for person to person transmission and focus their efforts, investigations, and interventions accordingly.en_US
dc.description.statementofresponsibilityby Erica Zhou.en_US
dc.format.extent73 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleInteractive visualization and discovery of possible transmission routes of Clostridioides difficileen_US
dc.typeThesisen_US
dc.description.degreeM. Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.identifier.oclc1227276694en_US
dc.description.collectionM.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienceen_US
dspace.imported2021-01-06T18:31:09Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentEECSen_US


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