GGPONC：一个基于临床实践指南的具有丰富元数据的德语医学文本语料库
GGPONC: A Corpus of German Medical Text with Rich Metadata Based on Clinical Practice Guidelines
摘要：
缺乏可公开访问的文本语料库是自然语言处理取得进展的主要障碍。不幸的是，对于医疗应用来说，除英语之外的所有语言社区都资源不足。在这项工作中，我们提出了GGPONC（德国肿瘤学NLP语料库指南计划），一个基于肿瘤学临床实践指南的免费分发的德语语料库。该语料库是有史以来最大的德国医学文献库之一。与临床文件不同，临床指南不包含任何患者相关信息，因此可以在没有数据保护限制的情况下使用。此外，GGPONC是第一个涵盖大型医学子领域各种条件的德语语料库，并提供各种元数据，如文献参考和证据水平。通过应用和评估德语文本的现有医疗信息抽取管道，我们能够将医学语言的使用与其他医学和非医学语料库进行比较。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
