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dc.contributor.authorRahman, Asmita
dc.date.accessioned2014-03-04T20:24:59Z
dc.date.available2014-03-04T20:24:59Z
dc.date.issued2011-12
dc.identifier.otherrahman_asmita_201112_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/rahman_asmita_201112_ms
dc.identifier.urihttp://hdl.handle.net/10724/27798
dc.description.abstractABSTRACT In the fast growing world of information, the amount of medical knowledge is growing at an exponential level. It has now become a very difficult task for a regular person to keep up with all the new discoveries and updates in this domain. This thesis describes an approach to semantically retrieve and distribute the medical data/information to the respective health records (people). This system comprises of sample health records and health publications from PubMed. The system performs a semantic matchmaking algorithm to find the relevant publications in PubMed for any particular health record (profile) using BioPortal Ontologies and UMLS. It then assigns a rank based on a semantic ranking algorithm and displays the results to the user. Our system empowers the users and enables them to discover hidden but relevant information. The result of the evaluation clearly proves that our system retrieves all the relevant information better than syntactic searches.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectSemantic Matchmaking
dc.subjectMatchmaking algorithm
dc.subjectSemantic Ranking
dc.subjectKnowledge Discovery
dc.subjectElectronic Health Records
dc.subjectHealth Publications
dc.subjectOntology.
dc.titleSemantic retrieval and distribution of relevant medical knowledge
dc.typeThesis
dc.description.degreeMS
dc.description.departmentComputer Science
dc.description.majorComputer Science
dc.description.advisorIsmailcem Budak Arpinar
dc.description.committeeIsmailcem Budak Arpinar
dc.description.committeeThiab R. Taha
dc.description.committeeKhaled Rasheed


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