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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
MEDSYNDIKATE--a natural language system for the extraction of medical information from findings reports
Udo Hahn1, Martin Romacker, Stefan Schulz
1Text Knowledge Engineering Lab, Freiburg University, Werthmannplatz 1, D-79104, Freiburg, Germany. hahn@coling.uni-freiburg.de
Abstract:
MEDSYNDIKATE is a natural language processor, which automatically acquires medical information from findings reports. In the course of text analysis their contents is transferred to conceptual representation structures, which constitute a corresponding text knowledge base. MEDSYNDIKATE is particularly adapted to deal properly with text structures, such as various forms of anaphoric reference relations spanning several sentences. The strong demands MEDSYNDIKATE poses on the availability of expressive knowledge sources are accounted for by two alternative approaches to acquire medical domain knowledge (semi)automatically. We also present data for the information extraction performance of MEDSYNDIKATE in terms of the semantic interpretation of three major syntactic patterns in medical documents.
