title: Semantic tagging for medical knowledge tracking.
abstract: We propose a semantic tagger that provides high level concept information for phrases in clinical documents, which enriches medical information tracking system that support decision making or quality assurance of medical treatment. In this paper, we have tried to deal with patient records written by doctors rather than well-formed documents such as Medline abstracts. In addition, annotating clinical text on phrases semantically rather than syntactically has been attempted, which are at higher level granularity than words that have been the target for most tagging work.
authors.affiliation: Dept. of Comput. Sci., Inf. & Commun. Univ., Daejeon, Korea.
authors.forename: Hyeju
authors.initials: H
authors.lastname: Jang
authors.forename: Sa Kwang
authors.initials: SK
authors.lastname: Song
authors.forename: Sung Hyon
authors.initials: SH
authors.lastname: Myaeng
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003201:Computers; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D019359:Knowledge; D008037:Linguistics; D016239:MEDLINE; D008390:Markov Chains; D009323:Natural Language Processing; D012660:Semantics; D012984:Software; D013358:Subject Headings; D009626:Terminology as Topic