Center for Data-Driven Discovery in Biomedicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Department of Library and Information Science, Sungkyunkwan University, Seoul, Republic of Korea.
J Am Med Inform Assoc. 2020 Oct 1;27(10):1612-1624. doi: 10.1093/jamia/ocaa107.
The Unified Medical Language System (UMLS) is 1 of the most successful, collaborative efforts of terminology resource development in biomedicine. The present study aims to 1) survey historical footprints, emerging technologies, and the existing challenges in the use of UMLS resources and tools, and 2) present potential future directions.
We collected 10 469 bibliographic records published between 1986 and 2019, using a Web of Science database. graph analysis, data visualization, and text mining to analyze domain-level citations, subject categories, keyword co-occurrence and bursts, document co-citation networks, and landmark papers.
The findings show that the development of UMLS resources and tools have been led by interdisciplinary collaboration among medicine, biology, and computer science. Efforts encompassing multiple disciplines, such as medical informatics, biochemical sciences, and genetics, were the driving forces behind the domain's growth. The following topics were found to be the dominant research themes from the early phases to mid-phases: 1) development and extension of ontologies and 2) enhancing the integrity and accessibility of these resources. Knowledge discovery using machine learning and natural language processing and applications in broader contexts such as drug safety surveillance have recently been receiving increasing attention.
Our analysis confirms that while reaching its scientific maturity, UMLS research aims to boundary-span to more variety in the biomedical context. We also made some recommendations for editorship and authorship in the domain.
The present study provides a systematic approach to map the intellectual growth of science, as well as a self-explanatory bibliometric profile of the published UMLS literature. It also suggests potential future directions. Using the findings of this study, the scientific community can better align the studies within the emerging agenda and current challenges.
统一医学语言系统(UMLS)是生物医学术语资源开发中最成功、最具协作性的努力之一。本研究旨在:1)调查 UMLS 资源和工具的使用历史足迹、新兴技术和现有挑战;2)提出潜在的未来方向。
我们使用 Web of Science 数据库收集了 1986 年至 2019 年期间发表的 10469 条文献记录。采用图分析、数据可视化和文本挖掘技术,分析领域级引用、主题类别、关键词共现和爆发、文献共引网络和里程碑文献。
研究结果表明,UMLS 资源和工具的开发一直得到医学、生物学和计算机科学等跨学科合作的引领。涵盖医学信息学、生物化学和遗传学等多个学科的努力是该领域发展的驱动力。从早期到中期,以下主题被发现是主要的研究主题:1)本体论的开发和扩展;2)提高这些资源的完整性和可访问性。最近,使用机器学习和自然语言处理进行知识发现以及在更广泛的背景(如药物安全监测)中的应用受到了越来越多的关注。
我们的分析证实,尽管 UMLS 研究已经达到了科学成熟阶段,但它旨在跨越更广泛的生物医学背景。我们还对该领域的编辑和作者提出了一些建议。
本研究提供了一种系统的方法来绘制科学知识的增长图,以及对已发表 UMLS 文献的自我解释的文献计量学概况。它还提出了潜在的未来方向。利用本研究的结果,科学界可以更好地调整研究工作,以适应新兴议程和当前挑战。