GGPONC: A Corpus of German Medical Text with Rich Metadata Based on Clinical Practice Guidelines
July 13, 2020 ยท Declared Dead ยท ๐ International Workshop on Health Text Mining and Information Analysis
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Authors
Florian Borchert, Christina Lohr, Luise Modersohn, Thomas Langer, Markus Follmann, Jan Philipp Sachs, Udo Hahn, Matthieu-P. Schapranow
arXiv ID
2007.06400
Category
cs.CL: Computation & Language
Citations
28
Venue
International Workshop on Health Text Mining and Information Analysis
Last Checked
4 months ago
Abstract
The lack of publicly accessible text corpora is a major obstacle for progress in natural language processing. For medical applications, unfortunately, all language communities other than English are low-resourced. In this work, we present GGPONC (German Guideline Program in Oncology NLP Corpus), a freely distributable German language corpus based on clinical practice guidelines for oncology. This corpus is one of the largest ever built from German medical documents. Unlike clinical documents, clinical guidelines do not contain any patient-related information and can therefore be used without data protection restrictions. Moreover, GGPONC is the first corpus for the German language covering diverse conditions in a large medical subfield and provides a variety of metadata, such as literature references and evidence levels. By applying and evaluating existing medical information extraction pipelines for German text, we are able to draw comparisons for the use of medical language to other corpora, medical and non-medical ones.
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