MedSynD iKATe—a natural language system for the extraction of medical information from findings reports

Abstract

medSynD iKATe 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. medSynD iKATe is particularly adapted to deal properly with text structures, such as various forms of anaphoric reference relations spanning several sentences. The strong demands medSynD iKATe 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 medSynD iKATe in terms of the semantic interpretation of three major syntactic patterns in medical documents.