title: Medical document anonymization with a semantic lexicon.
abstract: We present an original system for locating and removing personally-identifying information in patient records. In this experiment, anonymization is seen as a particular case of knowledge extraction. We use natural language processing tools provided by the MEDTAG framework: a semantic lexicon specialized in medicine, and a toolkit for word-sense and morpho-syntactic tagging. The system finds 98-99% of all personally-identifying information.
authors.affiliation: Medical Informatics Division, University Hospital of Geneva, ISSCO, University of Geneva.
authors.forename: P
authors.initials: P
authors.lastname: Ruch
authors.forename: R H
authors.initials: RH
authors.lastname: Baud
authors.forename: A M
authors.initials: AM
authors.lastname: Rassinoux
authors.forename: P
authors.initials: P
authors.lastname: Bouillon
authors.forename: G
authors.initials: G
authors.lastname: Robert
mesh_terms: D016494:Computer Security; D003219:Confidentiality; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D012660:Semantics