Publikation

Negation Detection in Clinical Reports Written in German

Viviana Cotik, Roland Roller, Feiyu Xu, Hans Uszkoreit, Klemens Budde, Danilo Schmidt

In: Proceedings of the Fifth Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM2016). Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM-2016) befindet sich COLING 2016 December 12 Osaka Japan The COLING 2016 Organizing Committee 2016.

Abstrakt

An important subtask in clinical text mining tries to identify whether a clinical finding is expressed as present, absent or unsure in a text. This work presents a system for detecting mentions of clinical findings that are negated or just speculated. The system has been applied to two different types of German clinical texts: clinical notes and discharge summaries. Our approach is built on top of NegEx, a well known algorithm for identifying non-factive mentions of medical findings. In this work, we adjust a previous adaptation of NegEx to German and evaluate the system on our data to detect negation and speculation. The results are compared to a baseline algorithm and are analyzed for both types of clinical documents. Our system achieves an F1-Score above 0.9 on both types of reports.

Projekte

Weitere Links

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence