title: MedSynDiKATe--design considerations for an ontology-based medical text understanding 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 general system architecture we present 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.
authors.affiliation: Freiburg University, Text Knowledge Engineering Lab.
authors.forename: U
authors.initials: U
authors.lastname: Hahn
authors.forename: M
authors.initials: M
authors.lastname: Romacker
authors.forename: S
authors.initials: S
authors.lastname: Schulz
mesh_terms: D005069:Evaluation Studies as Topic; D008499:Medical Records; D009323:Natural Language Processing; D012984:Software; D017432:Unified Medical Language System