GGPONC: A Corpus of German Medical Text with Rich Metadata Based on Clinical Practice Guidelines

TL;DR

GGPONC is a large, freely accessible German medical text corpus based on clinical guidelines, enriched with metadata, facilitating NLP research in low-resource medical languages.

Contribution

This work introduces GGPONC, the first extensive German medical corpus with rich metadata, derived from clinical guidelines, enhancing NLP resources for non-English medical texts.

Findings

Existing medical NLP pipelines perform comparably on GGPONC and other corpora.

GGPONC enables detailed analysis of German medical language use.

The corpus supports future NLP applications in German healthcare.

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.