论文标题
纸质平原:使医学研究论文通过自然语言处理对医疗保健消费者的平易近人
Paper Plain: Making Medical Research Papers Approachable to Healthcare Consumers with Natural Language Processing
论文作者
论文摘要
当寻求未涵盖的患者友好文件(例如医学小册子)的信息时,医疗保健消费者可能会转向研究文献。但是,阅读医学论文可能是一个充满挑战的经历。为了改善医疗论文的访问,我们介绍了一个新颖的交互式接口纸平面,其中四个功能由自然语言处理提供支持:不熟悉的术语的定义,位于原位的普通语言部分摘要,一个关键问题的集合,指导读者回答通道,以及答案通道的普通语言摘要。我们评估纸质平原,发现使用纸质平原的参与者比使用典型的PDF阅读器的参与者更容易阅读和理解研究论文而不会损失纸张理解。总的来说,研究结果表明,指导读者了解相关段落,并提供简单的语言摘要或“ GIST”,而原始纸张内容可以使阅读医学论文更加容易,并使读者更有信心与这些论文有关。
When seeking information not covered in patient-friendly documents, like medical pamphlets, healthcare consumers may turn to the research literature. Reading medical papers, however, can be a challenging experience. To improve access to medical papers, we introduce a novel interactive interface-Paper Plain-with four features powered by natural language processing: definitions of unfamiliar terms, in-situ plain language section summaries, a collection of key questions that guide readers to answering passages, and plain language summaries of the answering passages. We evaluate Paper Plain, finding that participants who use Paper Plain have an easier time reading and understanding research papers without a loss in paper comprehension compared to those who use a typical PDF reader. Altogether, the study results suggest that guiding readers to relevant passages and providing plain language summaries, or "gists," alongside the original paper content can make reading medical papers easier and give readers more confidence to approach these papers.