Visual analysis of research hotspots and trends in traditional Chinese medicine for depression in the 21st century: A bibliometric study based on citespace and VOSviewer.

Depression long been a key concern for scholars worldwide; however, the field of depression has not received sufficient attention in traditional Chinese medicine. It was not until the 21st century that research into depression gradually entered a period of rapid development, with an increasing number of academic studies published in major journals. However, one limitation of this field is that no scholars have yet summarised the development process and key research issues. Therefore, the present study aimed to summarise the research trends and progress in this field, providing relevant information and presenting potential future research directions for subsequent researchers. Literature in this field was searched from January 1, 2000 to April 20, 2024 in the Web of Science Core Collection database, to analyse the current status of the literature and publication trends. Bibliographic information, including study authors, organisations, keywords, countries, references, citations, and co-citations, was extracted using CiteSpace and VOSviewer software for quantitative analysis, visual mapping, and scientific evaluation. A total of 921 papers were included, with a significant increase in the number of publications from 2017 to 2021, and a stable number of more than 140 publications between 2022 and 2023, with publications in these two years accounting for 31.38 % of the total. The Journal of Ethnopharmacology had the highest number of publications (97) and citations (2067), as well as the highest number of co-citations (1369). China (847 publications, 13256 citations), Beijing University of Chinese Medicine (90 publications, 1232 citations), and Qin Xuemei (30 publications, 759 citations) were the most prolific and influential countries, organisations, and authors in the field, respectively. Keyword clustering co-occurrence analysis revealed nine different clusters with good homogeneity. The top three clusters were randomised controlled trials, traditional Chinese medicine, and hippocampal neurogenesis. In the timeline analysis of keywords, from 2000 to 2010, keywords in this field were concentrated on hippocampal neurology and forced swimming test as clustering axes of Traditional Chinese Medicine. From 2010 to 2020, the research hotspots focused on randomised controlled trials and hippocampal neurogenesis. After 2020, keywords became more focused on network pharmacology. In addition, the occurrence time of explosive keywords were distributed before 2010 and after 2020. Before 2010, these keywords included the forced swimming test, Tail Suspension Test, Chronic Cold Stress, Neural Regeneration, and Banxia Houpu Decoction. Conversely, network Pparmacology and Molecular Docking arose as key buzzwords starting in 2020. This study comprehensively analysed and summarised the research hotspots and trends in this field of research in the 21st century from a bibliometric perspective, further generating a series of visual graphs to help researchers understand the current research status, potential collaborators, collaborating institutions, and potential future research hotspots in this field.

Song C ，Chen K ，Jin Y ，Chen L ，Huang Z ... -  《Heliyon》

Research hotspots and frontiers of machine learning in renal medicine: a bibliometric and visual analysis from 2013 to 2024.

The kidney, an essential organ of the human body, can suffer pathological damage that can potentially have serious adverse consequences on the human body and even affect life. Furthermore, the majority of kidney-induced illnesses are frequently not readily identifiable in their early stages. Once they have progressed to a more advanced stage, they impact the individual's quality of life and burden the family and broader society. In recent years, to solve this challenge well, the application of machine learning techniques in renal medicine has received much attention from researchers, and many results have been achieved in disease diagnosis and prediction. Nevertheless, studies that have conducted a comprehensive bibliometric analysis of the field have yet to be identified. This study employs bibliometric and visualization analyses to assess the progress of the application of machine learning in the renal field and to explore research trends and hotspots in the field. A search was conducted using the Web of Science Core Collection database, which yielded articles and review articles published from the database's inception to May 12, 2024. The data extracted from these articles and review articles were then analyzed. A bibliometric and visualization analysis was conducted using the VOSviewer, CiteSpace, and Bibliometric (R-Tool of R-Studio) software. 2,358 papers were retrieved and analyzed for this topic. From 2013 to 2024, the number of publications and the frequency of citations in the relevant research areas have exhibited a consistent and notable increase annually. The data set comprises 3734 institutions in 91 countries and territories, with 799 journals publishing the results. The total number of authors contributing to the data set is 14,396. China and the United States have the highest number of published papers, with 721 and 525 papers, respectively. Harvard University and the University of California System exert the most significant influence at the institutional level. Regarding authors, Cheungpasitporn, Wisit, and Thongprayoon Charat of the Mayo Clinic organization were the most prolific researchers, with 23 publications each. It is noteworthy that researcher Breiman I had the highest co-citation frequency. The journal with the most published papers was "Scientific Reports," while "PLoS One" had the highest co-citation frequency. In this field of machine learning applied to renal medicine, the article "A Clinically Applicable Approach to Continuous Prediction of Future Acute Kidney Injury" by Tomasev N et al., published in NATURE in 2019, emerged as the most influential article with the highest co-citation frequency. A keyword and reference co-occurrence analysis reveals that current research trends and frontiers in nephrology are the management of patients with renal disease, prediction and diagnosis of renal disease, imaging of renal disease, and development of personalized treatment plans for patients with renal disease. "Acute kidney injury," "chronic kidney disease," and "kidney tumors" are the most discussed diseases in medical research. The field of renal medicine is witnessing a surge in the application of machine learning. On one hand, this study offers a novel perspective on applying machine learning techniques to kidney-related diseases based on bibliometric analysis. This analysis provides a comprehensive overview of the current status and emerging research areas in the field, as well as future trends and frontiers. Conversely, this study furnishes data on collaboration and exchange between countries, regions, institutions, journals, authors, keywords, and reference co-citations. This information can facilitate the advancement of future research endeavors, which aim to enhance interdisciplinary collaboration, optimize data sharing and quality, and further advance the application of machine learning in the renal field.

Li F ，Hu C ，Luo X 《-》

Bibliometric analysis of laryngeal cancer treatment literature (2003-2023).

Despite advancements in medical science, the 5-year survival rate for laryngeal squamous cell carcinoma remains low, posing significant challenges in clinical management. This study explores the evolution of key topics and trends in laryngeal cancer research. Bibliometric and knowledge graph analysis are utilized to assess contributions in treating this carcinoma and to forecast emerging research hotspots that may enhance future clinical outcomes. The findings aim to guide researchers by identifying new areas, providing valuable insights and innovative perspectives. Data were extracted from the Web of Science Core Collection database on December 1, 2023. Bibliometric and knowledge mapping analyses were conducted using software tools such as R-Studio 4.1.3, CiteSpace 6.1.R6, VOSviewer 1.6.18, and http://bibliometre.com.(Both CiteSpace 6.1.R6 and VOSviewer 1.6.18 are widely used bibliometric analysis software tools, each with distinct features and applications. CiteSpace primarily focuses on analyzing literature citation relationships and generating knowledge graphs to visualize research hotspots, trends, and knowledge structures. Its data sources include platforms such as Web of Science. While CiteSpace excels in presenting knowledge structures through its advanced visualization capabilities, it is relatively complex to operate and less efficient in processing large-scale datasets. As a result, it is frequently employed in exploring research trends across multiple disciplines. On the other hand, VOSviewer is designed to construct various types of bibliometric networks and is characterized by its intuitive and user-friendly interface. It supports a wide range of data sources and produces visually appealing and clear visualizations, making it particularly suitable for multi-disciplinary bibliometric research. Additionally, VOSviewer provides valuable insights that can inform scientific research decision-making. Overall, the two tools differ in terms of functionality, data sources, visualization effects, and operational complexity, offering researchers complementary options for bibliometric analysis based on their specific needs.) From this database, 800 papers were extracted using specific criteria. After narrowing the scope to English-language publications, this number was reduced to 775. To ensure data quality, conference papers, letters, and editorial materials were excluded, focusing only on original research papers and review articles. The analysis showed that 760 theoretical works and review papers were published in 96 academic journals by 4210 authors from 1148 institutions across 60 countries/regions. The United States emerged as the most significant contributor to laryngeal cancer research. The Croatian Rudjer Boskovic Institute was notable for having the highest publication and citation counts. Among individual researchers, Osmak, M was identified as the most prolific and cited. Predominant international collaborations occurred between European and American countries. The Head and Neck Science Journal was the most frequently co-cited publication. Major research themes encompassed morphological aspects, chemotherapy, and molecular pathway mechanisms in laryngeal cancer treatment. Current research hotspots include disease prognosis, models, clinical trials, tumor recurrence, and surveillance. Notably, targeted therapy and immunotherapy are rapidly advancing fields. There is an urgent need to enhance global scholarly communication as the pursuit of effective laryngeal cancer treatment progresses. Focused research on targeting indicators for this type of cancer remains vital. An impending surge in research is driven by investigations into biomarkers, microenvironmental genetic mechanisms, alternatives to systemic chemotherapy, minimally invasive surgery, and herbal medicine explorations.

Zhao Y ，Xue J 《Heliyon》

Global research hotspots and trends of iodinated contrast agents in medical imaging: a bibliometric and visualization analysis.

This study employs bibliometric methods to explore the global research dynamics of iodine contrast agents in medical imaging. Through the visualization of knowledge maps, it presents research progress and reveals the research directions, hotspots, trends, and frontiers in this field. Using Web of Science Core Collection database, CiteSpace and VOSviewer were employed to conduct a visual analysis of the global application of iodine contrast agents in medical imaging over the past four decades. The analysis focused on annual publication volume, collaboration networks, citation characteristics, and keywords. A total of 3,775 studies on the application of iodine contrast agents in medical imaging were included. The earliest paper was published in 1977, with a slight increase in publications from 1991 to 2004, followed by a significant rise after 2005. The United States emerged as the leading country in publication volume. Harvard University was identified as a globally influential institution with 126 publications. Although a large author collaboration cluster and several smaller ones were formed, most collaborations between authors were relatively weak, with no high-density integrated academic network yet established. Pietsch Hubertus was the most prolific author, while Bae KT was the most highly co-cited author. The most highly cited journal was Radiology, with 2,384 citations. Co-occurrence analysis revealed that the top three keywords by frequency were "agent," "CT," and "image quality." Keyword clustering analysis showed that the top three clusters were "gadolinium," "gold nanoparticles," and "image quality." The timeline analysis indicated that clusters such as "gadolinium," "gold nanoparticles," "image quality," and "material decomposition" exhibited strong temporal continuity, while the keyword with the highest burst value was "digital subtraction angiography" (19.38). Burst term trend analysis suggested that recent research has been focusing on areas like "deep learning," "risk," "radiation dosage," and "iodine quantification." This study is the first to systematically reveal the global trends, hotspots, frontiers, and development dynamics of iodine contrast agents in medical imaging through the use of CiteSpace and VOSviewer. It provides a novel perspective for understanding the role of iodine contrast agents in imaging and offers valuable insights for advancing global research in medical imaging.

Liu Y ，Dong Y ，Xie F 《Frontiers in Medicine》

Knowledge graph and frontier trends in melanoma-associated ncRNAs: a bibliometric analysis from 2006 to 2023.

Malignant melanoma (MM) is a highly malignant skin tumor. Although research on non-coding RNAs (ncRNAs) of MM has advanced swiftly in recent years, no specific bibliometric analyses have been conducted on this topic. The present study aims to summarize the knowledge graphs and frontier trends and to provide new perspectives and direction of collaboration for researchers. Research data on melanoma and ncRNA published from January 1, 2006 to October 9, 2023 were retrieved and extracted from Web of Science. R Studio (Version 4.3.1), Scimago Graphica (Version 1.0.36), VOSviewer version (1.6.19), and Citespace (6.2.4R) were used to analyze the publications, countries, journals, institutions, authors, keywords, references, and other relevant data and to build collaboration network graphs and co-occurrence network graphs accordingly. A total of 1,222 articles were retrieved, involving 4,894 authors, 385 journals, 43,220 references, 2413 keywords, and 1,651 institutions in 47 countries. The average annual growth rate in the number of articles was 25.02% from 2006 to 2023; among all the journals, Plos One had the highest number of publications and citations, which are 42 publications and 2,228 citations, respectively. Chinese researchers were the most prolific publishers in this field, having published a total of 657 articles, among which 42 were published by Shanghai Jiao Tong University, which was the most productive institution. In recent years, the most explored keywords included long non-coding RNAs, immunotherapy, and exosm. According to the timeline chart of reference co-citation, "functional role" has been the most explored hotspot since 2015, and human cancer is a newly emerged hotspot after 2021. Through a bibliometric analysis, this study included all publications on ncRNAs and melanoma that were published in English from 2006 to 2023 in Web of Science to analyze the trends in the number of publications, international research focuses, and the direction of collaboration. The results of this study may provide information on knowledge graph, frontier trends and identify research topics in melanoma. More current research proved that ncRNA plays a crucial role in the biological behavior of melanoma including proliferation, invasion, metastasis, drug resistance, etc. With the development of research on ncRNA and melanoma, ncRNA may great potential in development of early diagnosis, targeted therapy and efficacy evaluation in the future. The results of this study also provide new perspectives and research partners for researchers in this field.

Wang R ，Zhu XY ，Wang Y 《Frontiers in Oncology》