Dietrich Georg, Ertl Maximilian, Fette Georg, Kaspar Mathias, Krebs Jonathan, Mackenrodt Daniel, Störk Stefan, Puppe Frank
Chair of Computer Science VI, Würzburg University, Germany.
Service Center Medical Informatics, University Hospital Würzburg, Germany.
Stud Health Technol Inform. 2017;243:152-156.
Patient recruitment for clinical trials is a laborious task, as many texts have to be screened. Usually, this work is done manually and takes a lot of time. We have developed a system that automates the screening process. Besides standard keyword queries, the query language supports extraction of numbers, time-spans and negations. In a feasibility study for patient recruitment from a stroke unit with 40 patients, we achieved encouraging extraction rates above 95% for numbers and negations and ca. 86% for time spans.
临床试验的患者招募是一项艰巨的任务，因为必须筛选大量文本。通常，这项工作是手动完成的，需要花费大量时间。我们开发了一个系统，可使筛选过程自动化。除了标准的关键词查询外，查询语言还支持提取数字、时间跨度和否定词。在一项从拥有40名患者的中风单元招募患者的可行性研究中，我们在数字和否定词的提取率方面达到了令人鼓舞的95%以上，时间跨度的提取率约为86%。
