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Semi-Automatic Terminology Generation for Information Extraction from German Chest X-Ray Reports

机译:来自德国胸部X射线报告的信息提取的半自动术语

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Extraction of structured data from textual reports is an important sub-task for building medical data warehouses for research and care. Many medical and most radiology reports are written in a telegraphic style with a concatenation of noun phrases describing the presence or absence of findings. Therefore a lexico-syntactical approach is promising, where key terms and their relations are recognized and mapped on a predefined standard terminology (ontology). We propose a two-phase algorithm for terminology matching: In the first pass, a local terminology for recognition is derived as close as possible to the terms used in the radiology reports. In the second pass, the local terminology is mapped to a standard terminology. In this paper, we report on an algorithm for the first step of semi-automatic generation of the local terminology and evaluate the algorithm with radiology reports of chest X-ray examinations from Wurzburg university hospital. With an effort of about 20 hours work of a radiologist as domain expert and 10 hours for meetings, a local terminology with about 250 attributes and various value patterns was built. In an evaluation with 100 randomly chosen reports it achieved an F1-Score of about 95% for information extraction.
机译:从文本报告中提取结构化数据是建立研究和关怀的医疗数据仓库的重要子任务。许多医疗和大多数放射学报告都以电汇编写的,其具有描述存在或缺乏调查结果的名词短语的串联。因此,一个词典语法方法是有前途的,其中关键术语及其关系被认可并映射到预定的标准术语(本体)。我们提出了一种两阶段术语匹配算法:在第一阶段中,识别的本地术语尽可能接近放射学报告中使用的术语。在第二次通过中,局部术语被映射到标准术语。在本文中,我们报告了局部术语半自动生成第一步的算法,评价胸茨堡大学医院胸X射线检查的放射学报告算法。努力占据放射科医师作为领域专家的工作和10小时的会议,建立了大约250个属性和各种价值模式的本地术语。在具有100个随机选择的报告的评估中,它达到了约95%的F1分数,以进行信息提取。

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