Department of Psychiatry, Faculty of Medicine, University of Kelaniya, Sri Lanka.
Asian J Psychiatr. 2022 Mar;69:102986. doi: 10.1016/j.ajp.2021.102986. Epub 2021 Dec 30.
This bibliometric analysis aimed to identify active research areas and trends in machine learning applications within the psychiatric literature. An exponential growth in the number of related publications indexed in Web of Science during the last decade was noted. Document co-citation analysis revealed 10 clusters of knowledge, which included several mental health conditions, albeit with visible structural overlap. Several influential publications in the co-citation network were identified. Keyword trends illustrated a recent shift of focus from "psychotic" to "neurotic" conditions. Despite a relative lack of literature from the developing world, a recent rise in publications from Asian countries was observed. DATA AVAILABILITY: Bibliographic data for this study were downloaded from the Web of Science. The search strategy is included in the Supplementary file.
这项文献计量分析旨在确定精神科文献中机器学习应用的活跃研究领域和趋势。注意到在过去十年中，相关出版物在 Web of Science 中的索引数量呈指数级增长。文献共被引分析揭示了 10 个知识集群，其中包括几种心理健康状况，但存在明显的结构重叠。在共被引网络中确定了几个有影响力的出版物。关键词趋势表明，最近的研究重点从“精神病性”向“神经症性”条件转移。尽管来自发展中国家的文献相对较少，但观察到来自亚洲国家的出版物最近有所增加。数据可用性：本研究的文献计量数据从 Web of Science 下载。搜索策略包含在补充文件中。
