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dc.contributor.authorPatton, Evan
dc.contributor.authorMcGuinness, Deborah
dc.date.accessioned2022-02-18T02:34:46Z
dc.date.available2022-02-18T02:34:46Z
dc.date.issued2014-10-19
dc.identifier.other96
dc.identifier.urihttp://archive.tw.rpi.edu/media/latest/medinet-ls.pdf
dc.identifier.urihttps://hdl.handle.net/20.500.13015/4498
dc.description.abstractWe are developing prototypes that explicate our vision of connecting personal medical data to scientific literature as well as to emerging grey literature (e.g., community forums) to help people find and understand information relevant to complex medical journeys. We focus on robust combinations of natural language processing along with linked data and knowledge representation to build knowledge graphs that help people make sense of current conditions and enable new manners of scientific hypothesis generation. We present our work in the context of a breast cancer use case. We discuss the benefits of biomedical linked data resources and describe some potential assistive technology for navigating rich, diverse medical content.
dc.relation.urihttps://tw.rpi.edu/project/redrugs
dc.subjectRepurposing Drugs with Semantics
dc.titleConnecting Science Data Using Semantics and Information Extraction


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