title: Extracting semantic predications from Medline citations for pharmacogenomics.
abstract: We describe a natural language processing system (Enhanced SemRep) to identify core assertions on pharmacogenomics in Medline citations. Extracted information is represented as semantic predications covering a range of relations relevant to this domain. The specific relations addressed by the system provide greater precision than that achievable with methods that rely on entity co-occurrence. The development of Enhanced SemRep is based on the adaptation of an existing system and crucially depends on domain knowledge in the Unified Medical Language System. We provide a preliminary evaluation (55% recall and 73% precision) and discuss the potential of this system in assisting both clinical practice and scientific investigation.
authors.affiliation: Lister Hill National Center for Biomedical Communications, National Library of Medicine Bethesda, Maryland 20894, USA.
authors.forename: Caroline B
authors.initials: CB
authors.lastname: Ahlers
authors.forename: Marcelo
authors.initials: M
authors.lastname: Fiszman
authors.forename: Dina
authors.initials: D
authors.lastname: Demner-Fushman
authors.forename: François-Michel
authors.initials: FM
authors.lastname: Lang
authors.forename: Thomas C
authors.initials: TC
authors.lastname: Rindflesch
mesh_terms: D019295:Computational Biology; D019389:Cytochrome P-450 CYP2D6 / Q000235:genetics / Q000378:metabolism; D006801:Humans; D016239:MEDLINE; D009323:Natural Language Processing; D010597:Pharmacogenetics / Q000706:statistics & numerical data*; D012660:Semantics; D017432:Unified Medical Language System
chemical_list: D019389:Cytochrome P-450 CYP2D6