Bibliometric analysis of research trends on rotary dryers using the VOSviewer application base on the Scopus database

PurposePostoperative pancreatic fistula is a common and serious complication after pancreaticoduodenectomy that significantly impairs patient recovery and prognosis. Despite extensive research, the field lacks systematic bibliometric visualization analyses, which hinders comprehensive understanding of its research landscape, evolutionary trends and key advancements. This study aims to address this gap by systematically analyzing relevant literature to clarify global research patterns and emerging directions.MethodsA bibliometric analysis was conducted on literature regarding postoperative pancreatic fistula after pancreaticoduodenectomy published from January 2006 to December 2024. Data were retrieved from Web of Science Core Collection and Scopus databases. After removing duplicates, filtering by document type, language and time, and assessing eligibility, 4295 records were included. VOSviewer and Microsoft Excel were used to analyze publication trends, collaboration networks, core author contributions, keyword clustering and co-citation networks.ResultsThe number of publications increased steadily with original research articles dominating. Japan the United States China Italy and Germany were the top contributing countries while England had the highest average citation rate per article. University of Verona, Universiteit van Amsterdam, and Heidelberg University were key contributing institutions. Core research themes included postoperative pancreatic fistula classification and definition, risk factors, preventive measures, and surgical technique comparison.ConclusionThis study comprehensively maps the global research landscape and trends of postoperative pancreatic fistula after pancreaticoduodenectomy. The findings provide valuable insights for identifying research hotspots and guiding future studies, thereby promoting standardized and systematic advancement in this field.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00423-025-03939-7.

Introduction: The convergence of Industry 4.0 and 5.0 within the health sector heralds a transformative era, leveraging advanced technologies and human intelligence to redefine healthcare delivery. This evolution not only revolutionizes patient care and outcomes but also revolutionizes hospital financing, enabling cost reduction, improved efficiency, and enhanced revenue streams through the strategic integration of artificial intelligence (AI), Internet of Things (IoT), and blockchain technologies. Aim: Through a bibliometric analysis, this paper seeks to unravel the evolving trends in research within hospital financial and Health Industry 4.0/5.0. Materials & Methods: Bibliometric analysis was performed using the search results from Scopus database, Bibliometrix package in R Studio, and Vosviewer. Result & Discussion: 178 studies were eligible for analysis from the search on Scopus database. Cooccurrence analysis revealed 5 clusters of keywords in the topic of hospital financing and Health Industry 4.0/5.0. The overlay cooccurrence map showed a shift of the main research topic from focusing on cost analysis and reduction to applying more advanced technologies and addressing privacy concerns. Conclusions: The increasing impact of Industry 4.0 and 5.0 on hospital financing is indicated by an increasing scholarly focus towards applying more sophisticated technology in hospital financing.

The purpose of this study is to describe research trend data related to the implementation of PBL in science education. Article metadata was collected from the SCOPUS database, and 131 relevant articles were selected in 2013-2022. Data were analyzed using the Systematic Literature Network Analysis (SLNA) method with the VOSViewer application. Variables of bibliometric analysis, such as the number of articles and citations each year, the journals and authors with the most publications, countries, and networks of authors' cooperation, were determined based on metadata and analyzed descriptively. This research shows that the number of PBL research articles in science education during the 2013-2022 period fluctuated and tended to increase. The top keywords with the highest link strength are science, teacher, and technology. Recent research focuses on modules/e-modules, scientific literacy, natural science, and physics as important keywords. Future research related to the use of PBL learning has the potential to be developed in physics material and focuses on developing 21st-century skills such as creative thinking, critical thinking, communication, and collaboration. In addition, further research can focus on developing the knowledge and skills of prospective teachers in implementing PBL models that are integrated with 21st-century skills.

Background and Purpose: Higher education serves not merely as a means of imparting knowledge, skills, and societal values to students; it also offers individuals the chance to explore the world, discover their identity and position, gain a deeper understanding of others, and develop appropriate responses to diverse perspectives. Hence, it is vital to acknowledge and understand the significance of students’ identities as it is not an inherent or fixed concept; instead, it emerges and transforms through diverse academic experiences encountered by students from all around the world. The objective of this study is to examine various methods to identify the global research trends related to students’ identities in higher education. This bibliometric study examines various methods to identify the global research trends related to students’ identities in higher education, including annual publication output, leading countries, prolific authors, and co-occurring author keywords.
 
 Methodology: A bibliometric study was conducted by utilising VOSviewer software (version 1.6.18) in comprehending the worldwide studies on students’ identities in higher education. The study analysed publication trends from as far back as 1974 up to 2022, using data from the Scopus database. Data collection took place between July 1 and July 5, 2023, using the Scopus database. Data collection occurred between July 1 and July 5, 2023. The study examined publication trends, including time, author, and institution mapping, keyword clustering, and identifying emerging terms.
 Findings: The findings revealed a notable increase in researchers' attention towards studying students' identities in higher education, reflected in a rise in related articles. Various theoretical frameworks, including Community of Practice, Acculturation, Self-Concept, Habitus, and Situated Learning, have been extensively examined to provide insights into understanding these identities. These frameworks underscore the impact of social, cultural, and psychological factors on how students perceive themselves and engage within academic settings.
 
 Contributions: This bibliometric analysis enhances our understanding of students' identities in higher education, guiding future research and providing useful advice for professionals, researchers, and policymakers in the educational sector. Exploring students' identities offers valuable insights into collaborative networks and potential partners, facilitating further advancements in the field.
 
 Keywords: Students’ identities, higher education, bibliometrics analysis.
 
 Cite as: Tun, N., & Khairuddin, Z. (2024). Exploring 50 years of research on students’ identities in higher education context: A bibliometric analysis. Journal of Nusantara Studies, 9(1), 368-394. http://dx.doi.org/10.24200/jonus.vol9iss1pp368-394

Mapping the evolving landscape of lecanemab research in Alzheimer's Disease: A bibliometric analysis.

Since the 1990s, work life balance has been widely studied by scientists, so research results are increasing from year to year. Employees must not only perform effectively at work but also have a personal life that includes their family and community. To keep their human resources employed, organizations need to pay close attention to employees' ability to combine their professional and personal lives. Many working people currently feel that there is not enough balance between work and personal life in the workplace. The goal of this study is to determine how far the study of work-life balance has come. This study will give readers a comprehensive picture of the dynamics in play right now and reveal the state of the work-life balance literature. The importance of this research is to see the tendency of previous researchers in studying the theory of work life balance. In addition, it provides a systematic analysis of the work life balance literature using bibliometric analysis. A descriptive analysis approach is used in this study. The Scopus database is used for the data collection for this study. A total of 2,446 documents from 2012 to 2022 made up the database utilized to review this research. The VOSviewer application is used on the devices, and the data are exported in CSV format. This study will map the theory of work-life balance research, publishing trends, theoretical underpinnings, cited journals, often used research keywords and clusters in research groups. Additionally, this research offers a summary of the subject under discussion so that it can be updated in subsequent studies. According to Scopus analysis, the fields of management, management, and business research in the United States play the largest role in work-life balance studies. Analysis was performed with VOSviewer, where work life balance research has seen erratic developments in research papers. Various trends discuss work life balance using a bibliometric mapping approach. Researchers still rarely employ this research trend for future research to be able to use these findings as hints about trends. The few journals that published these studies in 2022 demonstrate that there is still a dearth of work-life balance research data.

Background: Genomic disease surveillance has become an essential and transformative tool in public health. It enhances our ability to detect, monitor, and control infectious diseases by providing real-time genetic information about pathogens. This advanced approach allows for more accurate identification of disease outbreaks, tracking the spread of infections, and understanding the evolution of pathogens over time. Global genomic surveillance faces challenges with a lack of standardized data protocols and insufficient funding. Addressing privacy and ethical concerns about genetic data is crucial for building stakeholder trust and cooperation. Overcoming these obstacles is vital for maximizing the benefits of genomic surveillance in global public health protection. Aim: This study aimed to identify key research trends and authors in genomic disease surveillance. Methods: This study employed bibliometric analysis using data from the Scopus database, which was analyzed quantitatively with the biblioshiny software for bibliometric analysis. The R package offers functions for analyzing yearly outputs, country outputs, citations, collaboration networking, and publication trends. Results: Two thousand and sixty-two (2062) articles were retrieved from the Scopus database. The United States leads with a total of four hundred and three (403) publications. Giovanetti M. was the lead author with twenty (20) publications. The field of Medicine had the highest number of articles (867 publications). Notably, there was a significant increase in research output between the years 2017 and 2023, with the highest number of publications (202) in the latter. The top-ranked article, written by Quick J, has garnered an impressive 998 citations. Conclusion: This bibliometric analysis of scientific publications on genomic disease surveillance from 2006 to 2024 identified significant research trends, thematic hotspots, and patterns of international collaboration. The study observed a notable increase in research output from developed countries such as the United States United Kingdom, China, Australia, and Brazil, with less output from developing countries. These findings highlight the critical role of genomic surveillance in the detection, monitoring, and response to infectious diseases, particularly in the context of future pandemics.

Background: ICU patients with critical conditions are generally intubated due to their inability to breathe independently. These patients require assistance from nurses in meeting their basic needs, one of which is oral hygiene. ICU nurses use several protocols when doing oral hygiene in intubated patients. Purpose: This study was conducted to reveal the trend of research on oral hygiene in intubated patients in the last two decades through bibliometric analysis. Methods: This study is a quantitative research. The research publications were collected from the Scopus and PubMed databases through the Publish or Perish application. Then, for further analysis, the VOSViewer application was used to create visualization maps of co-occurring terms that include the research themes. Results: There were a total of 88 publications from two databases in the last two decades that discussed oral hygiene in intubated patients. Visualization in VOSViewer illustrates five main clusters on oral hygiene-intubated patients. Most of the publication themes were oral hygiene protocols and the relationship between the oral hygiene and VAP incidence. However, suction toothbrush as one of the oral hygiene protocol did not appear in the co-occurring terms in the first search; therefore, the researchers conducted a separate search about this term. Conclusions: Based on the analysis, the most common themes used are oral hygiene protocols and the relationship between oral hygiene and VAP in the last two decades. However, research on suction toothbrush as one of the protocols is still lacking, so it can be used as a novelty in conducting further research.

This paper has reviewed the global research on the pandemic critical care research during the COVID-19 from 2020 to 2022. To this end, a bibliometric and cluster analysis by full counting has been carried out using VOSviewer software and bibliographic data extracted from the Scopus database. The research found and studied 2778 documents. The types of research documents were limited to an article (81.46%), a letter (9.43%), an editorial (3.92%), a note (3.92%), a conference paper (0.90), and a short survey (0.04%). The results show an incessant increase in the number of research documents published and citations received during the COVID-19 pandemic. The U.S., U.K., Italy, and France have been shown to be the most productive countries, and there is a predominance of European institutions supporting and fostering research on pandemic critical care. Cecconi, M. (Italy) and Shankar-Hari, M. (U.K.) produced the highest number of research documents. Mapping of citation, co-citation, co-authorship, and keyword cooccurrence highlighted the hotspot, knowledge structure, and important themes. Citation dynamics for the top-cited research documents revealed static discourse. By reviewing the evolutionary trends of pandemic critical care research investigated factors, such as the influential works, main research topics, and the research frontiers, this paper reveals the scientific literature production's main research objectives and directions that could be addressed and explored in future studies. This paper reveals the scientific literature production's main research objectives and directions that could be addressed and explored in future studies after reviewing the evolutionary trends of pandemic critical care research during the COVID-19 and the investigated factors, such as influential works, main research topics, and research frontiers.

The purpose of this study is to identify and analyze articles that examine students' critical thinking abilities that have been published in several reputable international journals published in period 2011-2020 using bibliometric analysis. The research was conducted using a systematic mapping method in 4 stages: (1) searching articles using the Publish or Perish (PoP) application in the Scopus database, (2) classifying articles for bibliometric analysis, (3) checking and filling in article metadata and (4) conducting bibliometric analysis using the VOSviewer application. The results of the bibliometric analysis yielded 5 findings, as follows: (1) the trend of publication of critical thinking skills has fluctuated from 2011-2020; (2) the ten most contributing journals have published 46 articles up to 2020; (3) the ten most cited articles resulted in 669 citations; (4) The four highest order keywords that are most widely used in critical thinking skills articles are critical thinking abilities, thinking abilities and students; (5) There are 6 writers who research critical thinking skills the most but have not seen collaboration between the 6 writers; It can be concluded that student critical thinking abilities in the world of education are being researched even though they have fluctuated over the last 10 years.

With the advent of big data, artificial intelligence (AI)is rapidly emerging as a promising avenue for pain management research. Integrating big data analytics, machine learning, and intelligent algorithms within AI can facilitate several significant advancements in healthcare. These include the ability to provide clinical diagnoses of pain, risk prediction, and the development of precision medicine. The number of articles on the application of AI to pain management is on the rise. However, there needs to be more information regarding the quality of the research output in this area, as well as the current hotspots and trends in research. At the same time, no bibliometric metrics have been identified that assess scientific progress in this area. In order to gain an understanding of the current status and potential future directions in the application of AI within the field of pain management, it is first necessary to undertake a visual and analytical study of the relevant research. A bibliometric and visual analysis was conducted to identify research hotspots and trends in the application of AI in pain management over the past 30years. The data information source was the SCI-EXPANDED subset database of the WOS database. A manual search was conducted of all articles and reviews from the database's inception to June 29, 2024. The search was limited to English language sources. A bibliometric analysis was conducted using VOSviewer, CiteSpace, and Bibliometrix (an R-Tool of R-Studio). The analysis encompassed a range of aspects related to the global publication status of papers in the field, including countries and regions, institutions, authors, journals, keywords, and co-cited references. A total of 970 published papers were obtained for this study. The articles were published in 496 journals by 5679 authors affiliated with 2030 academic institutions in 84 countries or regions. From 2014 to 2024, there was a gradual increase in the number of papers published within this field, with 97% of the total published papers. The United States and China contribute the most to this growth. The most prominent research institutions are Harvard University, the University of California system, and Harvard Medical School. At the author level, Mork, Paul Jarle, Bach, and Kerstin of the Norwegian University of Science & Technology (NTNU) were identified as the authors with the highest research output. Breiman, L. of the University of California, Berkeley, emerged as the most influential author, exhibiting the highest co-citation frequency. From the perspective of journals, the Journal of Medical Internet Research, Scientific Reports, PAIN, PLOS ONE, and SPINE are the primary core journals in the field. They have a high number of published papers and co-citation frequency. Furthermore, of the 46,170 co-cited references, Loetsch J's "Machine learning in pain research," published in PAIN in 2018, had the highest number of co-citations, thus making it the most influential article in the study. Combining keywords and co-cited references for analysis leads to the conclusion that using AI for accurate clinical monitoring and risk prediction, clinical diagnosis and classification, and providing personalized treatment plans and care measures for pain has become a current research hotspot and a future trend. Machine learning, deep learning, artificial neural networks, and clinical decision support systems in artificial intelligence are frequently mentioned and commonly used to build predictive models. These are also hot research topics and trends in the field. The field of research on using AI for pain management is experiencing unprecedented growth and development. This study offers a novel perspective on applying AI to pain management, which may inform researchers' selection of potential journals and institutions to collaborate with. Furthermore, this study furnishes researchers with the requisite data to comprehend the present state of research, research focal points, and research tendencies in this field, thereby facilitating the implementation of AI in pain management.

The intersection of Cybersecurity and AI has garnered increasing attention in recent years due to the growing importance of securing digital assets in an interconnected world. This bibliometric analysis aims to provide valuable insights into the research trends and developments within this interdisciplinary domain. Using data extracted from the Scopus database, a total of 501 papers were selected and analyzed to uncover key patterns and themes. The methodology involved conducting a comprehensive literature search using specific keywords related to Cybersecurity and AI applications. The initial search yielded 736 papers, which were subsequently filtered to include research articles, conference papers, editorial papers, and review papers, resulting in the final dataset of 501 papers. The analysis of publication trends revealed a remarkable surge in research output since 2015, indicating the escalating interest in this field. Collaboration patterns among researchers and institutions were analyzed through co-authorship networks, highlighting a well-connected research community that fosters knowledge exchange. Keyword analysis exposed common areas of application, such as network security, deep learning, and the Internet of Things, underscoring the importance of AI technologies in enhancing Cybersecurity measures. Furthermore, examination of the most cited documents showcased influential contributions that have shaped the trajectory of Cybersecurity and AI research. The study emphasizes the significance of Cybersecurity and AI applications research, considering the ever-increasing reliance on technology in various aspects of modern life. By integrating AI technologies, Cybersecurity measures can be fortified with automated threat detection, adaptive defense mechanisms, and proactive risk mitigation, thereby bolstering overall cybersecurity resilience. The findings of this bibliometric analysis have several implications for researchers and policymakers. Researchers can leverage the identified trends and gaps to explore new research directions and potential collaborations. Policymakers can utilize these insights to make informed decisions regarding resource allocation for research initiatives aimed at addressing emerging Cybersecurity challenges. This bibliometric analysis provides a comprehensive overview of the evolving landscape of Cybersecurity and AI applications research. It underscores the growing importance of this interdisciplinary field and its potential to reshape the future of cybersecurity. As technology continues to advance, the integration of AI in Cybersecurity will play a pivotal role in safeguarding digital assets and ensuring the secure functioning of critical systems in an increasingly interconnected world.

This article is written to analyze the research trends regarding the integration of the Problem Based Learning (PBL) model in laboratory practical activities over the past 10 years (2014–2023). The method employed is Bibliometric Analysis, supported by the VOSviewer application. The analysis focused on titles and abstracts, encompassing 961 scientific articles from international journals indexed in Scopus over the last decade. Data collection was performed through searches using the keyword "Problem Based Learning in Laboratory Activities." The search results reveal network formation, overlays, and trend direction graphs over the past 10 years. The research yields the following data: 1) The total number of publication articles based on keywords is 961 documents, which are filtered down to 453 documents, 2) The country with the highest contribution to published articles is the USA with 194 documents, 3) Co-occurrence analysis shows variations in article topics with six clusters, and 4) Overlay Visualization indicates that articles on laboratory activities tend to focus on the learning system, student-related aspects, curriculum, and problem-solving

Abstract— The digital transformation process in businesses operates within the data and knowledge cycle. This cycle ensures that all functions and units of an business collaborate effectively to achieve maximum efficiency from technological advancements. Recently, industrial metaverse technology has emerged as a new catalyst in the digital transformation process. This technology integrates with various other technologies to generate a virtual work environment akin to the physical workspace. The objective of this study is to identify the technologies and processes that industrial metaverse technology collaborates with and to provide a vision for researchers and businesses interested in this field. To achieve this objective, a bibliometric analysis was conducted on studies indexed in the Web of Science (WoS) and Scopus databases using the keyword "industrial metaverse." The analysis included a total of 60 studies: 44 from the Scopus database and 16 from the WoS database. A comprehensive examination of these 60 studies was performed, with data compiled manually and analyzed using the Vosviewer application. The study concluded that industrial metaverse technology is associated with processes such as smart production, employee-technology collaboration, ensuring the functionality of the data and knowledge cycle infrastructure, employee training, and environmental sustainability. Additionally, technologies such as digital twins, blockchain, virtual reality (VR), augmented reality (AR), Industrial Internet of Things (IIOT), and artificial intelligence (AI) form the infrastructure of industrial metaverse technology. Keywords— Digital transformation, Industrial metaverse, knowledge management, technology and innovation management, Industry 5.0

The study aimed to conduct a bibliometric analysis to examine patterns and trends observed in scientific articles on using herbal anti-inflammatory agents. Data were gathered from the Scopus database. In total, 121 articles on herbal anti-inflammatory drugs were examined through bibliometric analysis using the (RStudio®) and VOSviewer application. In the Scopus database, 121 articles on using herbal remedies to treat inflammation were included in this study. Moreover, China has produced the most research articles. The Journal of Ethnopharmacology, Molecules, and Molecules are the three most-read journals. The Journal of Ethnopharmacology demonstrates the highest level of productivity based on its citation count and h-index. Regarding publications on this topic, Li J is regarded as a leading figure. Articles by Li J have received the most citations (143), followed by those published by Li X (134). This study can be used as a reference by researchers when conducting studies on medicinal plants used as anti-inflammatory agents. The findings of this study also make it easier for researchers to locate a substantial global network of academics and promote collaboration in this area.