A fine-grained corpus annotation schema of German nephrology records

Roland Roller; Hans Uszkoreit; Feiyu Xu; Laura Seiffe; Michael Mikhailov; Oliver Staeck; Klemens Budde; Fabian Halleck; Danilo Schmidt

In: Proceedings of the Clinical Natural Language Processing Workshop (ClinicalNLP). Clinical Natural Language Processing Workshop (ClinicalNLP-2016), located at Coling 2016, December 11, Osaka, Japan, The COLING 2016 Organizing Committee, 2016.


In this work we present a fine-grained annotation schema to detect named entities in German clinical data of chronically ill patients with kidney diseases. The annotation schema is driven by the needs of our clinical partners and the linguistic aspects of German language. In order to generate annotations within a short period, the work also presents a semi-automatic annotation which uses additional sources of knowledge such as UMLS, to pre-annotate concepts in advance. The presented schema will be used to apply novel techniques from natural language processing and machine learning to support doctors treating their patients by improved information access from unstructured German texts.


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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence