OBJECTIVES To identify major research subjects and trends in medical informatics research based on the current set of core medical informatics journals. METHODS Analyzing journals in the Web of Science (WoS) medical informatics category together with related categories from the years 2013 to 2017 by using a smart local moving algorithm as a clustering method for identifying the core set of journals. Text mining analysis with binary counting of abstracts from these journals published in the years 2006 to 2017 for identifying major research subjects. Building clusters based on these terms for the complete time period as well as for the periods 2006-2008, 2009-2011, 2012-2014, and 2015-2017 for identifying trends. RESULTS The identified cluster includes 17 core medical informatics journals. By text mining of these journals, 224,992 different terms in 14,414 articles were identified covering 550 specific key terms. Based on these key terms five clusters were identified: "Biomedical Data Analysis," "Clinical Informatics," "EHR and Knowledge Representation," "Mobile Health," and "Organizational Aspects of Health Information Systems." No shifts in the clusters were observed between the first two 3-year periods. In the third period, some terms like "mobile phone," "mobile apps," and "message" appear. Also, in the third period, a "Clinical Informatics" cluster appears and persists in the fourth period. In the fourth period, a rearrangement of clusters was observed. CONCLUSIONS Beside classical subjects of medical informatics on organizing, representing, and analyzing data, we observed new developments in the context of mobile health and clinical informatics. These subjects tended to grow over the past years, and we can expect this trend to continue.

中文翻译：

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医学信息学的研究主题和研究趋势。

目的根据当前的核心医学信息学期刊集，确定医学信息学研究的主要研究主题和趋势。方法使用智能本地移动算法作为聚类方法来识别Web of Science（WoS）医学信息学类别和相关类别的期刊，以识别核心期刊集。在2006年至2017年出版的这些期刊中进行文本挖掘分析并对摘要进行二进制计数，以识别主要研究主题。在整个时间段以及2006-2008年，2009-2011年，2012-2014年和2015-2017年期间，基于这些术语构建集群以识别趋势。结果确定的集群包括17种核心医学信息学期刊。通过对这些期刊进行文本挖掘，得出224，确定了14,414篇文章中的992个不同术语，涵盖550个特定关键术语。基于这些关键术语，确定了五个类别：“生物医学数据分析”，“临床信息学”，“ EHR和知识表示”，“移动健康”和“健康信息系统的组织方面”。在头两个三年期之间，没有观察到集群的变化。在第三阶段，会出现“移动电话”，“移动应用程序”和“消息”之类的术语。同样，在第三阶段中，“临床信息学”集群出现并持续到第四阶段。在第四阶段，观察到簇的重排。结论除了有关医学信息学的经典主题之外，有关组织，表示和分析数据的信息，我们在移动健康和临床信息学的背景下观察到了新的发展。这些主题在过去几年中趋于增长，我们可以预期这种趋势将继续下去。