Medical document anonymization with a semantic lexicon.
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.
Ruch
P
P
Medical Informatics Division, University Hospital of Geneva, ISSCO, University of Geneva.
Baud
R H
RH
Rassinoux
A M
AM
Bouillon
P
P
Robert
G
G
D016494:Computer Security; D003219:Confidentiality; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D012660:Semantics