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

机译:具有患者,干预和结果多层次注释的语料库,支持医学文献的语言处理

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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:我们提供了描述临床随机对照试验的医学文章的5,000个带批注的摘要。注释包括描述所招募的患者人群的文本范围,所研究的干预措施以及与之比较的干预措施以及测量的结果(“ PICO *要素”)。这些跨度将在更细粒度的级别上进一步注释,例如,对其中的各个干预进行标记并映射到结构化的医学词汇表上。我们从具有不同水平的专业知识和成本的各种工人那里获得了注释。我们详细描述了数据收集过程和语料库本身。然后,我们概述了一组具有挑战性的NLP任务,这些任务将有助于医学文献的搜索和循证医学的实践。

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