论文标题
nlnde：两种语言 - 纳尔德域特殊者的西班牙医疗文件的方式
NLNDE: The Neither-Language-Nor-Domain-Experts' Way of Spanish Medical Document De-Identification
论文作者
论文摘要
自然语言处理在医疗领域具有巨大的潜力，最近导致了这一领域的大量研究。但是，安全处理医疗文件的先决条件，例如患者笔记和临床试验，是对隐私敏感信息的正确识别。在本文中，我们描述了我们的NLNDE系统，我们参与了Meddocan竞争，这是Iberlef 2019的医学文档匿名任务。我们解决了从西班牙数据中检测和分类为序列标签问题的受保护健康信息的任务，并研究了我们的神经网络的不同嵌入方法。尽管处理了非标准的语言和领域设置，但NLNDE系统在竞争中取得了令人鼓舞的结果。
Natural language processing has huge potential in the medical domain which recently led to a lot of research in this field. However, a prerequisite of secure processing of medical documents, e.g., patient notes and clinical trials, is the proper de-identification of privacy-sensitive information. In this paper, we describe our NLNDE system, with which we participated in the MEDDOCAN competition, the medical document anonymization task of IberLEF 2019. We address the task of detecting and classifying protected health information from Spanish data as a sequence-labeling problem and investigate different embedding methods for our neural network. Despite dealing in a non-standard language and domain setting, the NLNDE system achieves promising results in the competition.
