Advanced Search
DSpace@MIT

Was the patient cured? : understanding semantic categories and their relationship in patient records

Research and Teaching Output of the MIT Community

Show simple item record

dc.contributor.advisor Ozlem Uzuner and Peter Szolovits. en_US
dc.contributor.author Sibanda, Tawanda Carleton en_US
dc.contributor.other Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. en_US
dc.date.accessioned 2007-04-03T17:11:13Z
dc.date.available 2007-04-03T17:11:13Z
dc.date.copyright 2006 en_US
dc.date.issued 2006 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/37097
dc.description Includes bibliographical references (leaves 103-107). en_US
dc.description Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006. en_US
dc.description.abstract In this thesis, we detail an approach to extracting key information in medical discharge summaries. Starting with a narrative patient report, we first identify and remove information that compromises privacy (de-identification); next we recognize words and phrases in the text belonging to semantic categories of interest to doctors (semantic category recognition). For disease and symptoms, we determine whether the problem is present, absent, uncertain, or associated with somebody else (assertion classification). Finally, we classify the semantic relationships existing between our categories (semantic relationship classification). Our approach utilizes a series of statistical models that rely heavily on local lexical and syntactic context, and achieve competitive results compared to more complex NLP solutions. We conclude the thesis by presenting the design for the Category and Relationship Extractor (CaRE). CaRE combines our solutions to de-identification, semantic category recognition, assertion classification, and semantic relationship classification into a single application that facilitates the easy extraction of semantic information from medical text. en_US
dc.description.statementofresponsibility by Tawanda Carleton Sibanda. en_US
dc.format.extent 107 leaves en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights 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. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582
dc.subject Electrical Engineering and Computer Science. en_US
dc.title Was the patient cured? : understanding semantic categories and their relationship in patient records en_US
dc.title.alternative Semantic interpretation of medical discharge summaries en_US
dc.type Thesis en_US
dc.description.degree M.Eng. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. en_US
dc.identifier.oclc 84844278 en_US


Files in this item

Name Size Format Description
84844278.pdf 5.984Mb PDF Preview, non-printable (open to all)
84844278-MIT.pdf 5.979Mb PDF Full printable version (MIT only)

This item appears in the following Collection(s)

Show simple item record

MIT-Mirage