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The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews

机译:在线应用程序的开发和评估以帮助从图形中提取数据以用于系统评价

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摘要

>Background: The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from graphs in PDF files is particularly challenging, as the process is usually completely manual, and reviewers need sometimes to revert to holding a ruler against the page to read off values: an inherently time-consuming and error-prone process. >Methods: To mitigate some of the above problems we integrated and customised two existing JavaScript libraries to create a new web-based graphical data extraction tool to assist reviewers in extracting data from graphs. This tool aims to facilitate more accurate and timely data extraction through a user interface which can be used to extract data through mouse clicks. We carried out a non-inferiority evaluation to examine its performance in comparison with participants’ standard practice for extracting data from graphs in PDF documents. >Results: We found that the customised graphical data extraction tool is not inferior to users’ (N=10) prior standard practice. Our study was not designed to show superiority, but suggests that, on average, participants saved around 6 minutes per graph using the new tool, accompanied by a substantial increase in accuracy. >Conclusions: Our study suggests that the incorporation of this type of tool in online systematic review software would be beneficial in facilitating the production of accurate and timely evidence synthesis to improve decision-making.
机译:>背景:需要准确地进行基础研究报告所依赖的系统评价结果的数据提取。为了提高可靠性,建议两名研究人员独立进行数据提取。从PDF文件中的图形中提取统计数据特别具有挑战性,因为该过程通常是完全手动的,并且审阅者有时需要恢复到将标尺靠在页面上才能读取值:这是固有的耗时且容易出错的过程。 >方法:为缓解上述问题,我们集成并定制了两个现有的JavaScript库,以创建一个新的基于Web的图形数据提取工具,以帮助审阅者从图形中提取数据。该工具旨在通过用户界面促进更准确,及时的数据提取,该界面可用于通过单击鼠标来提取数据。我们进行了一项非劣质性评估,以与参与者从PDF文档中的图形提取数据的标准做法进行比较,以检查其性能。 >结果:我们发现,定制的图形数据提取工具并不逊于用户先前(N = 10)的标准做法。我们的研究并不是为了显示优越性,而是表明,使用新工具,参与者平均每张图节省了大约6分钟的时间,同时准确性大大提高。 >结论:我们的研究表明,将这种类型的工具整合到在线系统评价软件中,将有利于促进准确,及时地生成证据以改善决策。

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