Abdelwahab Siddig Ibrahim, Taha Manal Mohamed Elhassan, Farasani Abdullah, Moshi Jobran M, Alshahrani Abrar Fahad, Assiri Ahmad, Alshahrani Saeed, Sultan Muhammad H, Sahli Khaled A, Shubaily Hussam M, Elrhima Omer Ahmed, Hassan Waseem
Health Research Center, Jazan University, Jazan, Saudi Arabia.
Department of Medical Laboratory Technology, Faculty of Nursing and Health Sciences, Jazan University, Jazan, Saudi Arabia.
J Robot Surg. 2025 Jul 8;19(1):364. doi: 10.1007/s11701-025-02542-8.
This study utilizes the Scopus database and adopts a multi-layered approach to provide a comprehensive and detailed overview of robotic surgery research. Specifically, three complementary strategies: (a) a title-abstract-keyword (TAK) search, (b) a title-specific search, and (c) a focused analysis of the top 100 most cited papers were employed. The TAK approach retrieved 49,026 publications, substantially surpassing the 8,029 identified via the title-only method, demonstrating that incorporating abstracts and keywords provides broader coverage. Analysis of prolific authors revealed Mottrie, A. as the most productive researcher in the TAK dataset, while Fukuda, T. led in the title-only set. Leading institutions such as the Cleveland Clinic Foundation and Yonsei University College of Medicine exhibited markedly higher outputs under TAK criteria. Country-level analysis confirmed the United States as the dominant contributor in both datasets, though absolute counts dropped significantly when limited to titles. The Journal of Robotic Surgery emerged as the most productive source across both methods. Funding sponsor analysis highlighted the National Natural Science Foundation of China as the leading funder, with the TAK dataset revealing greater international sponsorship diversity. Citation analysis of the top 100 most cited documents, spanning 1993-2021, showed an average of 279.6 citations per article, with recent papers (2018-2021) achieving unprecedented citation velocity, suggesting earlier peaks in influence for newer publications. Keyword analysis of the top 150 most frequently occurring terms in the title-specific dataset helped to map key research directions. From the title-based corpus, the 100 most cited papers were analyzed, reporting their total citations, citations per paper, and citations per year. A detailed author-level analysis was performed, including publication count, citation impact, and scholarly indices (h-index, g-index, m-index), complemented by visualizations of collaboration networks. Moreover, this study incorporates a co-word analysis of the top 100 cited papers, using unigrams, bigrams, and trigrams to illustrate central themes. The top 20 most cited papers are briefly discussed. The findings offer updated, actionable insights for researchers, clinicians, and policymakers seeking to navigate this rapidly advancing field.
本研究利用Scopus数据库，并采用多层次方法，以全面、详细地概述机器人手术研究。具体而言，采用了三种互补策略：(a) 标题-摘要-关键词（TAK）搜索，(b) 特定标题搜索，以及 (c) 对被引频次最高的100篇论文进行重点分析。TAK方法检索到49,026篇出版物，大大超过仅通过标题方法识别出的8,029篇，这表明纳入摘要和关键词能提供更广泛的覆盖范围。对多产作者的分析显示，莫特里（Mottrie, A.）是TAK数据集中产出最多的研究者，而福田（Fukuda, T.）在仅基于标题的数据集里领先。克利夫兰诊所基金会和延世大学医学院等领先机构在TAK标准下的产出明显更高。国家层面的分析证实，美国在两个数据集中都是主要贡献者，不过仅限于标题时绝对数量大幅下降。《机器人手术杂志》在两种方法中都是产出最多的来源。资助赞助商分析突出了中国国家自然科学基金作为主要资助者，TAK数据集显示出更大的国际资助多样性。对1993年至2021年期间被引频次最高的100篇文献的引文分析表明，每篇文章平均被引279.6次，近期论文（2018 - 2021年）达到了前所未有的引文速度，这表明新出版物的影响力峰值出现得更早。对特定标题数据集中出现频率最高的150个术语进行关键词分析，有助于梳理关键研究方向。从基于标题的语料库中，对被引频次最高的100篇论文进行了分析，报告了它们的总被引频次、每篇论文的被引频次以及每年的被引频次。进行了详细的作者层面分析，包括发表数量、引文影响力和学术指标（h指数、g指数、m指数），并辅以合作网络可视化。此外，本研究对被引频次最高的100篇论文进行了共词分析，使用单字、双字和三字词来说明核心主题。简要讨论了被引频次最高的20篇论文。这些发现为试图在这个快速发展的领域中前行的研究人员、临床医生和政策制定者提供了最新的、可操作的见解。
