Wu Chieh-Chen, Su Chun-Hsien, Islam Md Mohaimenul, Liao Mao-Hung
Department of Healthcare Information and Management, School of Health Technology, Ming Chuan University, Taipei 333, Taiwan.
Department of Exercise and Health Promotion, College of Kinesiology and Health, Chinese Culture University, Taipei 111369, Taiwan.
Diagnostics (Basel). 2023 Jun 19;13(12):2109. doi: 10.3390/diagnostics13122109.
The applications of artificial intelligence (AI) in dementia research have garnered significant attention, prompting the planning of various research endeavors in current and future studies. The objective of this study is to provide a comprehensive overview of the research landscape regarding AI and dementia within scholarly publications and to suggest further studies for this emerging research field. A search was conducted in the Web of Science database to collect all relevant and highly cited articles on AI-related dementia research published in English until 16 May 2023. Utilizing bibliometric indicators, a search strategy was developed to assess the eligibility of titles, utilizing abstracts and full texts as necessary. The Bibliometrix tool, a statistical package in R, was used to produce and visualize networks depicting the co-occurrence of authors, research institutions, countries, citations, and keywords. We obtained a total of 1094 relevant articles published between 1997 and 2023. The number of annual publications demonstrated an increasing trend over the past 27 years. (39/1094, 3.56%), (38/1094, 3.47%), and (26/1094, 2.37%) were the most common journals for this domain. The United States (283/1094, 25.86%), China (222/1094, 20.29%), India (150/1094, 13.71%), and England (96/1094, 8.77%) were the most productive countries of origin. In terms of institutions, Boston University, Columbia University, and the University of Granada demonstrated the highest productivity. As for author contributions, Gorriz JM, Ramirez J, and Salas-Gonzalez D were the most active researchers. While the initial period saw a relatively low number of articles focusing on AI applications for dementia, there has been a noticeable upsurge in research within this domain in recent years (2018-2023). The present analysis sheds light on the key contributors in terms of researchers, institutions, countries, and trending topics that have propelled the advancement of AI in dementia research. These findings collectively underscore that the integration of AI with conventional treatment approaches enhances the effectiveness of dementia diagnosis, prediction, classification, and monitoring of treatment progress.
人工智能(AI)在痴呆症研究中的应用已引起广泛关注,促使当前和未来的研究计划开展各种研究工作。本研究的目的是全面概述学术出版物中关于人工智能与痴呆症的研究概况,并为这一新兴研究领域提出进一步的研究建议。我们在科学网数据库中进行了检索,以收集截至2023年5月16日发表的所有与人工智能相关的痴呆症研究的相关且被高度引用的英文文章。利用文献计量指标,制定了一种检索策略,必要时利用摘要和全文来评估文章标题的合格性。使用R语言中的统计软件包Bibliometrix工具来生成并可视化描绘作者、研究机构、国家、引用和关键词共现情况的网络。我们共获得了1997年至2023年间发表的1094篇相关文章。在过去27年中,年度出版物数量呈上升趋势。(39/1094,3.56%)、(38/1094,3.47%)和(26/1094,2.37%)是该领域最常见的期刊。美国(283/1094,25.86%)、中国(222/1094,20.29%)、印度(150/1094,13.71%)和英国(96/1094,8.77%)是产出最多的原产国。在机构方面,波士顿大学、哥伦比亚大学和格拉纳达大学的产出率最高。至于作者贡献,戈里斯·J·M、拉米雷斯·J和萨拉斯 - 冈萨雷斯·D是最活跃的研究人员。虽然在最初阶段,关注人工智能在痴呆症应用方面的文章数量相对较少,但近年来(2018 - 2023年)该领域的研究有了显著增长。本分析揭示了在研究人员、机构、国家和推动人工智能在痴呆症研究中发展的热门话题方面的关键贡献者。这些发现共同强调,人工智能与传统治疗方法的整合提高了痴呆症诊断、预测、分类和治疗进展监测的有效性。