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- W313890639 abstract "We present a framework for building a medical natural language processing (NLP) system capable of deep understanding of clinical text reports. The framework helps developers understand how various NLP-related efforts and knowledge sources can be integrated. The aspects considered include: 1) computational issues dealing with defining layers of intermediate semantic structures to reduce the dimensionality of the NLP problem; 2) algorithmic issues in which we survey the NLP literature and discuss state-of-the-art procedures used to map between various levels of the hierarchy; and 3) implementation issues to software developers with available resources. The objective of this poster is to educate readers to the various levels of semantic representation (e.g., word level concepts, ontological concepts, logical relations, logical frames, discourse structures, etc.). The poster presents an architecture for which diverse efforts and resources in medical NLP can be integrated in a principled way." @default.
- W313890639 created "2016-06-24" @default.
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- W313890639 date "2013-01-01" @default.
- W313890639 modified "2023-10-16" @default.
- W313890639 title "Hierarchical semantic structures for medical NLP." @default.
- W313890639 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/23920968" @default.
- W313890639 hasPublicationYear "2013" @default.
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