title: Automatic acquisition of sublanguage semantic schema: towards the word sense disambiguation of clinical narratives.
abstract: Natural language processing of clinical notes is challenging due to a high degree of semantic ambiguity. Previous research has uncovered ways to improve disambiguation accuracy using manually created rules of semantic sentence structure. However, applying a natural language processing system in a new clinical domain using this method is very labor intensive. This paper presents an automatic method of developing such disambiguation rules for a wide range of clinical domains. Our rules are based on the co-occurrence patterns of semantic types of terms unambiguously mapped to UMLS concepts by MetaMap. These patterns are combined into a sublanguage semantic schema that can be used by an existing natural language processing system such as MetaMap. The differences of co-occurrence patterns across clinical notes of different domains are presented here as evidence of clinical sublanguages.
authors.affiliation: Department of Biomedical Informatics, University of Utah, Salt Lake City, UT.
authors.forename: Olga
authors.initials: O
authors.lastname: Patterson
authors.forename: Sean
authors.initials: S
authors.lastname: Igo
authors.forename: John F
authors.initials: JF
authors.lastname: Hurdle
mesh_terms: D000465:Algorithms; D033262:Narration; D009323:Natural Language Processing; D010209:Paper; D012660:Semantics; D017432:Unified Medical Language System