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Utilizing the Wikidata System to Improve the Quality of Medical Content in Wikipedia in Diverse Languages: A Pilot Study

机译:利用Wikidata系统提高多种语言的Wikipedia中医疗内容的质量:一项初步研究

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Background: Wikipedia is an important source of medical information for both patients and medical professionals. Given its wide reach, improving the quality, completeness, and accessibility of medical information on Wikipedia could have a positive impact on global health.Objective: We created a prototypical implementation of an automated system for keeping drug-drug interaction (DDI) information in Wikipedia up to date with current evidence about clinically significant drug interactions. Our work is based on Wikidata, a novel, graph-based database backend of Wikipedia currently in development.Methods: We set up an automated process for integrating data from the Office of the National Coordinator for Health Information Technology (ONC) high priority DDI list into Wikidata. We set up exemplary implementations demonstrating how the DDI data we introduced into Wikidata could be displayed in Wikipedia articles in diverse languages. Finally, we conducted a pilot analysis to explore if adding the ONC high priority data would substantially enhance the information currently available on Wikipedia.Results: We derived 1150 unique interactions from the ONC high priority list. Integration of the potential DDI data from Wikidata into Wikipedia articles proved to be straightforward and yielded useful results. We found that even though the majority of current English Wikipedia articles about pharmaceuticals contained sections detailing contraindications, only a small fraction of articles explicitly mentioned interaction partners from the ONC high priority list. For 91.30% (1050/1150) of the interaction pairs we tested, none of the 2 articles corresponding to the interacting substances explicitly mentioned the interaction partner. For 7.21% (83/1150) of the pairs, only 1 of the 2 associated Wikipedia articles mentioned the interaction partner; for only 1.48% (17/1150) of the pairs, both articles contained explicit mentions of the interaction partner.Conclusions: Our prototype demonstrated that automated updating of medical content in Wikipedia through Wikidata is a viable option, albeit further refinements and community-wide consensus building are required before integration into public Wikipedia is possible. A long-term endeavor to improve the medical information in Wikipedia through structured data representation and automated workflows might lead to a significant improvement of the quality of medical information in one of the world’s most popular Web resources.
机译:背景:维基百科是患者和医务人员的重要医学信息来源。鉴于其覆盖面广,提高Wikipedia上医学信息的质量,完整性和可访问性可能会对全球健康产生积极影响。最新的有关临床上重要的药物相互作用的证据。我们的工作基于Wikidata,这是目前正在开发的基于Wikipedia的一种新颖的基于图形的数据库后端。方法:我们建立了一个自动化过程,用于集成来自国家健康信息技术协调员(ONC)高优先级DDI列表的数据进入Wikidata。我们建立了示例性的实现方式,展示了如何将我们引入Wikidata中的DDI数据以多种语言显示在Wikipedia文章中。最后,我们进行了一项试点分析,以探索添加ONC高优先级数据是否会大大增强Wikipedia当前可用的信息。结果:我们从ONC高优先级列表中获得了1150个唯一的交互。事实证明将来自Wikidata的潜在DDI数据集成到Wikipedia文章中非常简单,并产生了有用的结果。我们发现,尽管当前大多数有关药物的英文Wikipedia文章都包含详细说明禁忌症的章节,但只有一小部分文章明确提到了ONC高优先级列表中的相互作用伙伴。对于我们测试的91.30%(1050/1150)的相互作用对,与该相互作用物质相对应的2篇文章均未明确提及相互作用伙伴。对于7.21%(83/1150)的配对,在2条相关的Wikipedia文章中,只有1条提到了互动伙伴。对于仅1.48%(17/1150)的配对,这两篇文章都明确提及了互动伙伴。结论:我们的原型表明,通过Wikidata自动更新Wikipedia中的医学内容是可行的选择,尽管可以进行进一步的改进和在整个社区范围内。必须先建立共识,然后才能整合到公共Wikipedia中。通过结构化数据表示和自动化工作流进行的长期努力来改善Wikipedia中的医疗信息,可能会导致世界上最受欢迎的Web资源之一中医疗信息质量的显着提高。

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