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A Corpus with Multi -Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature

机译:具有多级注释的患者,干预和结果的语料库,以支持医学文献语言处理

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摘要

We present a corpus of 5,000 richly annotated abstracts of medical articles describing clinical randomized controlled trials. Annotations include demarcations of text spans that describe the Patient population enrolled, the Interventions studied and to what they were Compared, and the Outcomes measured (the 'PICO* elements). These spans are further annotated at a more granular level, e.g., individual interventions within them are marked and mapped onto a structured medical vocabulary. We acquired annotations from a diverse set of workers with varying levels of expertise and cost. We describe our data collection process and the corpus itself in detail. We then outline a set of challenging NLP tasks that would aid searching of the medical literature and the practice of evidence-based medicine.
机译:我们提出了一个5,000富豪摘要的医学文章摘要的语料库,描述了临床随机对照试验。注释包括描述注册患者人口的文本跨度的划分,所研究的干预措施以及比较的干预措施以及测量的结果('pico *元素)。这些跨度在更粒径的水平下进一步注释,例如,它们内部的个体干预措施被标记并映射到结构化医学词汇量上。我们从各种工人的注释获得了不同程度的专业知识和成本。我们详细描述了我们的数据收集过程和语料库本身。然后,我们概述了一套充满挑战的NLP任务,可以帮助寻求医学文献和基于证据的实践。

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