title: Creating knowledge repositories from biomedical reports: the MEDSYNDIKATE text mining system.
abstract: MEDSYNDIKATE is a natural language processor for automatically acquiring knowledge from medical finding reports. The content of these documents is transferred to formal representation structures which constitute a corresponding text knowledge base. The system architecture integrates requirements from the analysis of single sentences, as well as those of referentially linked sentences forming cohesive texts. The strong demands MEDSYNDIKATE poses to the availability of expressive knowledge sources are accounted for by two alternative approaches to (semi)automatic ontology engineering. We also present data for the knowledge extraction performance of MEDSYNDIKATE for three major syntactic patterns in medical documents.
authors.affiliation: Text Knowledge Engineering Lab, Freiburg University, D-79098 Freiburg, Germany.
authors.forename: Udo
authors.initials: U
authors.lastname: Hahn
authors.forename: Martin
authors.initials: M
authors.lastname: Romacker
authors.forename: Stefan
authors.initials: S
authors.lastname: Schulz
mesh_terms: D016001:Confidence Intervals; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods* / Q000592:standards; D019359:Knowledge; D008490:Medical Informatics / Q000379:methods* / Q000592:standards; D008491:Medical Informatics Applications; D015203:Reproducibility of Results