Analysis of Progress and Trends in Histology and Education Research Based on VOSviewer and Citespace (1936-2024).

The use of artificial intelligence (AI) technology has been growing in the management of intracranial aneurysms (IAs). This study aims to conduct a bibliometric analysis of researches on intracranial aneurysm management with artificial intelligence technology (IAMWAIT) to gain insights into global research trends and potential future directions. A comprehensive search of articles and reviews related to IAMWAIT, published from January 1, 1900 to July 20, 2023, was conducted using the Web of Science Core Collection (WoWCC).Visualizations of the bibliometric analysis were generated utilizing WPS Office, Scimago Graphica, VOSviewer, CiteSpace, and R. A total of 277 papers were included in the study. China emerged as the most prolific country in terms of publications, institutions, cooperating countries, and prolific authors. The United States garnered the highest number of total citations, institutions with the highest citations/H index, cooperating countries (n=9), and 3 of the top 10 cited papers. Both the total number of papers and the citation count exhibited a positive and significant correlation with the gross domestic product (GDP) of countries. The journal with the highest publication frequency was Frontiers in Neurology, while Stroke recorded the highest number of citations, H-index, and impact factor (IF). Areas of primary interest in IAMWAIT, leveraging AI technology, included rupture risk assessment/prediction, computer-assisted diagnosis, outcome prediction, hemodynamics, and laboratory research of IAs. IAMWAIT is an active area of research that has undergone rapid development in recent years. Future endeavors should focus on broader application of AI algorithms in various sub-fields of IAMWAIT to better suit the real world.

BackgroundWith the emerging information and communication technology, the field of medical informatics has dramatically evolved in health care and medicine. Thus, it is crucial to explore the global scientific research landscape on medical informatics.ObjectiveThis study aims to present a visual form to clarify the overall scientific research trends of medical informatics in the past decade.MethodsA bibliometric analysis of data retrieved and extracted from the Web of Science Core Collection (WoSCC) database was performed to analyze global scientific research trends on medical informatics, including publication year, journals, authors, institutions, countries/regions, references, and keywords, from January 1, 2011, to December 31, 2020.ResultsThe data set recorded 34,742 articles related to medical informatics from WoSCC between 2011 and 2020. The annual global publications increased by 193.86% from 1987 in 2011 to 5839 in 2020. Journal of Medical Internet Research (3600 publications and 63,932 citations) was the most productive and most highly cited journal in the field of medical informatics. David W Bates (99 publications), Harvard University (1161 publications), and the United States (12,927 publications) were the most productive author, institution, and country, respectively. The co-occurrence cluster analysis of high-frequency author keywords formed 4 clusters: (1) artificial intelligence in health care and medicine; (2) mobile health; (3) implementation and evaluation of electronic health records; (4) medical informatics technology application in public health. COVID-19, which ranked third in 2020, was the emerging theme of medical informatics.ConclusionsWe summarize the recent advances in medical informatics in the past decade and shed light on their publication trends, influential journals, global collaboration patterns, basic knowledge, research hotspots, and theme evolution through bibliometric analysis and visualization maps. These findings will accurately and quickly grasp the research trends and provide valuable guidance for future medical informatics research.

PurposeThis study systematically evaluated the intellectual progress in artificial intelligence (AI)-driven osteoporosis research between 2004 and 2024 by employing scientometric and visualization techniques. Through mapping knowledge domains and identifying emerging trends, it offered actionable recommendations and strategic insights to guide future scholarly endeavors.MethodsWe queried the Web of Science Core Collection for English-language articles and reviews published between January 1, 2004, and November 30, 2024, using search terms including “osteoporosis,” “deep learning,” “convolutional neural networks,” and “artificial intelligence.” Bibliometric data were processed via VOSviewer (v1.6.20), CiteSpace (v6.3.R1), Scimago Graphica (v 1.0.46), and the R package Bibliometrix to quantify annual publication trends, assess national/institutional contributions, evaluate journal/author impact metrics, and map keyword co-occurrence and burst dynamics.ResultsThe bibliometric analysis identified 408 publications (343 articles, 65 reviews) from 2004 to 2024, with a marked increase in output observed in 2024. China and the United States dominated scholarly productivity and citation impact. Leading institutions included the Technical University of Munich and Seoul National University, while Osteoporosis International emerged as the most influential journal. Prolific authors such as Thomas Baum demonstrated significant academic leadership. Keyword co-occurrence analysis revealed deep learning, artificial intelligence, and diagnosis as core research frontiers, signaling future technological and clinical priorities.ConclusionThis study represents the first comprehensive bibliometric analysis of research on artificial intelligence in the field of osteoporosis. It not only outlines the field’s development trajectory and emerging frontiers but also highlights the research focus on AI technologies, particularly deep learning. Furthermore, it emphasizes critical challenges in clinical translation, such as algorithm optimization, model interpretability, and ethical privacy concerns. By systematically identifying key contributors, collaborative networks, and evolving research fronts, this study provides a foundational roadmap for the field. It offers strategic priorities for researchers to address methodological gaps, serves as a reference for clinicians to understand the evolving technological toolkit, and provides a basis for policymakers to promote interdisciplinary collaboration.

An increasing number of studies have found that the gut microbiota was related to the occurrence and development of lung cancer. Nonetheless, publication trends and research hotspots in this field remain unknown. The study aimed to perform a bibliometric analysis to systematically identify publication trends and research hotspots in the field of gut microbiota and lung cancer research within a 12-year panorama. Publications related to the gut microbiota and lung cancer between 1 January 2011 and 25 October 2022 were retrieved from the Web of Science Core Collection (WoSCC) database. The online analytic tool of the WoSCC was used to analyze various bibliometric parameters. The bibliometrics website, CiteSpace, and VOSviewer were used to identify research trends and hotspots. A total of 375 publications related to the gut microbiota and lung cancer were extracted from WoSCC and identified for analysis. The number of annual publications has grown rapidly since 2018 and reached a peak in 2022. China was the most prolific country in this field, with 120 publications, followed by the United States (114), with the highest H-index of 31. Additionally, France ranked the highest with an average of 133 citations, while the leading institution and journal were the Unicancer and the International Journal of Molecular Sciences, respectively. Interestingly, Routy Bertrand was the most prolific author and also the most cited author in terms of H-index and citations. Reference and keyword burst detection indicated that the research hotspots mainly included 1) the gut microbiota directly affects the efficacy of immunotherapy for lung cancer, 2) the application of different gut bacteria on lung cancer, and 3) the mechanism of the gut microbiota on lung cancer. The findings of this study revealed the general publication trends and evolving research hotspots in the field of gut microbiota and lung cancer at a global level. The research hotspots focused on the clinical application of the gut microbiota combined with immunotherapy in lung cancer and its mechanism. The findings of this study provide new perspectives on the field, which may shed light on a beneficial impact on further etiological studies, diagnosis, and treatment for lung cancer.

ObjectiveTo explore the research hotspots in acupuncture treatment for myopia from 2014 to 2023.MethodsA comprehensive search was conducted in the Science Citation Index-Expanded (SCI-E) within the Web of Science Core Collection (WOSCC). We used CiteSpace 6.2.R6 to perform an in-depth analysis of the annual publication trends, prolific authors, institutions, keyword co-occurrences, and citation bursts. The study followed the PICO framework: the population (P) includes studies on patients with myopia, the intervention (I) is acupuncture treatment, no direct comparison (C) is applied, and the primary outcome (O) focuses on the identification of research trends and hotspots. Major outcome assessments included the analysis of publication trends over time, author productivity, influential journals, and the detection of emerging research topics through citation burst analysis. This bibliometric analysis was conducted on November 15, 2023.ResultsA total of 281 articles were included in the analysis. The trend line of annual publications over the past decade showed a modest increase, with a significant decline in 2019 and a surge in 2021. China and its affiliated academic institutions led globally in publication volume, with Ma Xiaopeng being the most prolific author and Fudan University the most influential institution. Ophthalmology emerged as the journal with the highest citation frequency. The most frequently occurring keywords were related to adolescent myopia and its complications. The developmental trajectory of the field is distinct, characterized by the integration of a single discipline.ConclusionAcupuncture shows promise as a complementary and alternative therapy for treating myopia, with growing interest in its clinical efficacy and mechanisms of action. Future research is likely to focus on optimizing treatment protocols and understanding the underlying biological mechanisms of acupuncture in myopia management.

Clinical relevance Meibomian gland dysfunction (MGD) is a major contributor to dry eye disease, affecting a large proportion of the population and leading to significant discomfort and ocular surface complications. Understanding trends in MGD research, including advancements in diagnostic technologies, therapeutic approaches, and interdisciplinary collaborations, is critical for improving clinical practices. Background This study aims to perform a bibliometric analysis on MGD to assess the current international status of meibomian gland dysfunction research and identify the most influential contributors (journals, countries, authors) and research topics in this field. Methods Data from studies on MGD were obtained using the Web of Science Core Collection on Science Citation Index Expanded database. Information regarding journals, titles, text, keywords, references, citations, author names, author institutions, and countries was recorded for each publication. The data were analysed using features of the Web of Science Core Collection website and the VOSviewer visualisation tool. Results A total of 1313 articles published between 1980 and 2024 were identified. The number of articles published in the last 10 years was found to be 3.01 times greater than in all previous years combined. The United States and China were the most productive countries, with the highest number of articles and citations. The most productive institutions were located in the United States and Japan. The most prolific author was Reiko Arita. The most frequently cited article was titled ‘The International Workshop on Meibomian Gland Dysfunction: Report of the Subcommittee on Anatomy, Physiology, and Pathophysiology of the Meibomian Gland’. Recent and emerging keywords include ‘intense pulsed light’, ‘meibography’, ‘lipiflow’, ‘artificial intelligence’, ‘meibogenesis’, ‘lipidomics’ and ‘human meibomian gland epithelium’, reflecting current trends in MGD research. Conclusions This study provides an overview of the current status and trends in MGD research, which may help clinicians and researchers better understand this field and predict its future directions.

As a promising neuromodulation technique, vagus nerve stimulation (VNS) has been utilized to treat diverse diseases and the number of VNS studies has grown prosperously. Nonetheless, publication trends and research hotspots in this field remain unknown. This study aimed to perform a bibliometric analysis to systematically identify publication trends and research hotspots in VNS research within a 20-year panorama. The Web of Science Core Collection (WoSCC) database was retrieved to screen eligible VNS-related publications from 2002 to 2021. The online analytic tool of the WoSCC database was used to analyze various bibliometric parameters, such as the number of annual publications, the output of countries/regions, journals, total citations, citations per publication, and the Hirsch index. Bibliometrics (http://bibliometric.com/) and CiteSpace (version 5.6.R3) were used to identify research trends and hotspots. A total of 7,283 publications were included for analysis. The annual number of publications increased stably but it increased significantly in recent years. The top five prolific countries were the United States, China, Germany, England, and France. The top five productive institutions were the University of California (Los Angeles), Harvard Medical School, Harvard University, University College London, and the University of Texas at Dallas. Notably, there was a geographical imbalance in countries and institutions. In addition, Epilepsy & Behavior, Epilepsia, and Plos One were the top three journals with the largest number of VNS publications. Michael P Kilgard was the most prolific author. Moreover, evolving research hotspots mainly included the effectiveness and mechanism of VNS on epilepsy, the role of VNS as an anti-inflammatory regulator, the application of VNS for psychiatric disorders, and the neuromodulation effect of VNS in headache management. This study has revealed the overall publication trends and evolving research trends at a global level over a 20-year panorama. The potential collaborators, institutions, hotspots, and future research trends are also identified in this field, which will help guide new research directions of VNS.

Objective: To analyse the research hotspots and trends of hip fracture complicated with sarcopenia. Methods: The Web of Science Core Collection database was searched from 1 January 2013 to 31 December 2023, and the relevant literature on hip fracture complicated with sarcopenia was searched, with CiteSpace 6.4.R 4 software used for data processing and analysis. Publication trends, keyword co-occurrence and clustering, and emergent word analysis were used to draw a map. Results: A total of 591 articles were retrieved from the Web of Science Core Collection, and the number of papers published in the field of hip fracture complicated with sarcopenia increased year by year. Currently, the research hotspots in this field mainly focus on the identification and diagnosis of hip fracture complicated with sarcopenia, the early intervention and management of key populations, and the promotion of rapid recovery in patients. Conclusion: In recent years, more attention has been paid to the field of hip fracture complicated with sarcopenia both domestically and internationally, and artificial intelligence technology (AI) has played an active role in this field, becoming a frontier trend in research. Predicting individuals with sarcopenia through AI reduces the incidence of hip fracture and sarcopenia. It is of great significance to guide patients with hip fracture and sarcopenia in utilising nursing applications for personalised care and rehabilitation treatment, thus reducing or even preventing the occurrence of sarcopenia. This is of great significance for improving the health level of the elderly population, enhancing the quality of life of older individuals, and achieving healthy aging.

The past decade has seen major advances in the use of artificial intelligence (AI) to solve various biomedical problems, including cancer. This has resulted in more than 6000 scientific papers focusing on AI in oncology alone. The expansiveness of this research area presents a challenge to those seeking to understand how it has developed. A scientific analysis of AI in the oncology literature is therefore crucial for understanding its overall structure and development. This may be addressed through bibliometric analysis, which employs computational and visual tools to identify research activity, relationships, and expertise within large collections of bibliographic data. There is already a large volume of research data regarding the development of AI applications in cancer research. However, there is no published bibliometric analysis of this topic that offers comprehensive insights into publication growth, co-citation networks, research collaboration, and keyword co-occurrence analysis for technological trends involving AI across the entire spectrum of oncology research. The purpose of this study is to investigate documents published during the last decade using bibliometric indicators and network visualization. This will provide a detailed assessment of global research activities, key themes, and AI trends over the entire breadth of the oncology field. It will also specifically highlight top-performing authors, organizations, and nations that have made major contributions to this research domain, as well as their interactions via network collaboration maps and betweenness centrality metric. This study represents the first global investigation of AI covering the entire cancer field and using several validated bibliometric techniques. It should provide valuable reference material for reorienting this field and for identifying research trajectories, topics, major publications, and influential entities including scholars, institutions, and countries. It will also identify international collaborations at three levels: micro (that of an individual researcher), meso (that of an institution), and macro (that of a country), in order to inform future lines of research. The Science Citation Index Expanded from the Web of Science Core Collection was searched for articles and reviews pertaining exclusively to AI in cancer from 2012 through 2022. Annual publication trends were plotted using Microsoft Excel 2019. CiteSpace and VOSViewer were used to investigate the most productive countries, researchers, journals, as well as the sharing of resources, intellectual property, and knowledge base in this field, along with the co-citation analysis of references and keywords. A total of 6757 documents were retrieved. China produced the most publications of any country (2087, 30.89%), and Sun Yat Sen University the highest number (167, 2.47%) of any institute. WEI WANG was the most prolific author (33, 0.49%). RUI ZHANG ranked first for highest betweenness centrality (0.21) and collaboration criteria. Scientific Reports was found to be the most prolific journal (208, 3.18%), while PloS one had the most co-citations (2121, 1.55%). Strong and ongoing citation bursts were found for keywords such as "tissue microarray", "tissue segmentation", and "artificial neural network". Deep learning currently represents one of the most cutting-edge and applicable branches of AI in oncology. The literature to date has dealt extensively with radiomics, genomics, pathology, risk stratification, lesion detection, and therapy response. Current hot topics identified by our analysis highlight the potential application of AI in radiomics and precision oncology.

The 2023 American Heart Association/American Stroke Association guideline and Wessels et al's 2024 randomized controlled trial highlight the potential benefits of intracranial nicardipine for aneurysmal subarachnoid hemorrhage (aSAH). This study aims to systematically identify the publication trends and research hotspots in this field through bibliometric analysis. Relevant publications were sourced from the Web of Science Core Collection (WoSCC). Bibliometric and visualization analyses were conducted using the online tools of the WoSCC database and CiteSpace 6.2.R6. Analysis of 28 articles published by 158 researchers from 55 institutions across 8 countries revealed an intermittent small-scale growth in annual publication volume from 1994 to 2024, with a continuous rise in annual citation volume since 2005, indicating growing interest in the field. Japan, Germany, and the United States of America (USA) were the most prolific and influential countries. Institutions such as Tokyo Women's Medical University showed particularly significant contributions. Kasuya Hidetoshi was the most prolific author. There was little global collaboration among countries, institutions, and authors, with distinct regional research characteristics: Japan and Germany focused on intracranial implants, while the USA concentrated on intrathecal injections. Major publishing and co-cited journals included Neurocritical Care, Acta Neurochirurgica, Journal of Neurosurgery, and Stroke. Popular keywords in 2024 included "preventing cerebral vasospasm", "delayed cerebral ischemia", "outcome events", and "clinical trials", revealing current research hotspots. This study maps the global clinical research landscape of intracranial application of nicardipine for aSAH from 1994 to 2024, providing valuable references and guidance for future research.

This study aims to use bibliometric methods to analyze highly cited nursing education articles on digital health, particularly those 100 top cited publications between 2020 and 2024, from the Web of Science (WOS) Core Collection. A retrospective bibliometric analysis was conducted. A bibliometric analysis of the most-cited digital health articles on nursing education in English with the highest citations. Data were sourced from the WOS Core Collection. Analysis was conducted using Excel and SPSS, while VOSviewer was used to visualize keyword trends. The analysis included examining journal distribution, author patterns, research types, methodologies, and keyword trends. The 100 most-cited articles were published between 1993 and 2024 by 91 different first authors from 22 countries. The United States contributed approximately 33% of the articles. Citation counts ranged from 198 to 1. Nurse Education Today was the most frequently cited journal. Review articles had higher average citations (50.96) compared to original articles (24.08). The focus of research has shifted from virtual reality (VR) to artificial intelligence (AI), with ChatGPT emerging as a new trend. Digital health is becoming a significant focus in nursing education research. While VR has been a dominant topic, AI is now emerging as a key research area. The findings provide insights into citation patterns and research trends, supporting future impactful studies in this field.

Dipeptidyl peptidase-4 (DPP-4) inhibitors are oral antihyperglycemic agents commonly prescribed for type 2 diabetes (T2DM). Due to the intricate relationship between glucose regulation and cardiovascular diseases (CVDs), DPP-4 inhibitors have attracted attention for their cardiovascular safety and efficacy. This bibliometric analysis aims to provide insights into the global research landscape on DPP-4 inhibitors and cardiovascular outcomes (CVOs). A bibliometric analysis was performed, using the Web of Science Core Collection. Data were analyzed using VOSviewer, CiteSpace, and Biblioshiny. The United States led in publication output, followed by Japan and China. Harvard University and the University of Toronto were the leading institutions. The most influential journals were Cardiovascular Diabetology and Diabetes Obesity & Metabolism. Darren K. McGuire was the most prolific author followed by Rury R. Holman. The most commonly occurring keyword was heart failure. Cluster analysis revealed key thematic areas in the field, including "incretin-based therapy," "dipeptidyl peptidase-4 inhibition," and "cardiovascular safety." Emerging clusters, such as "atrial fibrillation," have gained attention in recent years, highlighting evolving areas of investigation. This study underscores the importance of CVOs in the research on DPP-4 inhibitors. The high frequency of keywords such as "heart failure," along with recent terms like "mortality" and "risk," highlights a strong focus on cardiovascular safety and complications in the literature. Our analysis reflected that most studies address these critical aspects of cardiovascular health, discussing the potential role of DPP-4 inhibitors in mitigating adverse outcomes, particularly in patients with T2DM.

ObjectivesWe conducted a systematic and comprehensive bibliometric analysis of COVID-19-related medical imaging to determine the current status and indicate possible future directions.MethodsThis research provides an analysis of Web of Science Core Collection (WoSCC) indexed articles on COVID-19 and medical imaging published between 1 January 2020 and 30 June 2022, using the search terms “COVID-19” and medical imaging terms (such as “X-ray” or “CT”). Publications based solely on COVID-19 themes or medical image themes were excluded. CiteSpace was used to identify the predominant topics and generate a visual map of countries, institutions, authors, and keyword networks.ResultsThe search included 4444 publications. The journal with the most publications was European Radiology, and the most co-cited journal was Radiology. China was the most frequently cited country in terms of co-authorship, with the Huazhong University of Science and Technology being the institution contributing with the highest number of relevant co-authorships. Research trends and leading topics included: assessment of initial COVID-19-related clinical imaging features, differential diagnosis using artificial intelligence (AI) technology and model interpretability, diagnosis systems construction, COVID-19 vaccination, complications, and predicting prognosis.ConclusionsThis bibliometric analysis of COVID-19-related medical imaging helps clarify the current research situation and developmental trends. Subsequent trends in COVID-19 imaging are likely to shift from lung structure to function, from lung tissue to other related organs, and from COVID-19 to the impact of COVID-19 on the diagnosis and treatment of other diseases.Key Points• We conducted a systematic and comprehensive bibliometric analysis of COVID-19-related medical imaging from 1 January 2020 to 30 June 2022.• Research trends and leading topics included assessment of initial COVID-19-related clinical imaging features, differential diagnosis using AI technology and model interpretability, diagnosis systems construction, COVID-19 vaccination, complications, and predicting prognosis.• Future trends in COVID-19-related imaging are likely to involve a shift from lung structure to function, from lung tissue to other related organs, and from COVID-19 to the impact of COVID-19 on the diagnosis and treatment of other diseases.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00330-023-09498-z.

Background: Moyamoya angiopathy (MMA), which includes moyamoya disease (MMD) and moyamoya syndrome (MMS), is an uncommon cerebrovascular condition characterized by recurrent stroke. We carried out a bibliometric analysis to examine the development of and research trends in MMA research.Methods: Studies published between 2010 and 2019 on MMA were retrieved from the Web of Science Core Collection (WoSCC) on August 14, 2020, and bibliometric and visualization-based analyses were performed by using three different scientometric tools: HistCite, VOSviewer, and CiteSpace.Results: A total of 1,896 publications published in 384 journals by 6,744 authors, 1,641 institutions and 56 countries/regions were included in the analyses. Annual publication outputs increased from 2010 to 2019. The USA, Japan and China were three key contributors to this study field. Capital Medical University, Seoul National University, and Stanford University were three major institutions with larger numbers of publications. Zhang D, World Neurosurgery, Kuroda S, and STROKE were the most prolific author, prolific journal, top co-cited author and top co-cited journal, respectively. The top five keywords during this period were moyamoya disease, revascularization, stroke, children and surgery, while revascularization surgery and RNF213 were the most common frontier topics.Conclusions: In this study, the research trends of global scientific research on MMA over the past decade were systematically analyzed. The study can provide guidance for scholars who want to understand current trends in research in this area and new research frontiers.

BackgroundIn recent years, there have been an increasing number of studies on trigeminal neuralgia (TN). However, a scientific and comprehensive study of the current situation and trends in the field of TN research is lacking. The purpose of this study is to summarize and visualize the development, research hotspots, and future trends in TN based on a bibliometric approach.MethodsStudies on TN published from 2001 to 2021 were obtained from the Web of Science Core Collection (WoSCC). Bibliometrics, CiteSpace, and VOSviewer tools were used for bibliometric analysis and visualization.ResultsIn total, 4,112 documents were searched. The number of research articles in the field is generally on an upward trend, with the fastest growth in the number of articles from 2017 to 2020. Shanghai Jiao Tong University, Pittsburgh University, and Mayo Clinic are the three institutions with the most publications. Shiting Li and Zakrzewska JM are the most prolific author and top co-cited authors, respectively. The Journal of Neurosurgery is the most influential journal. The top 5 keywords in that time frame are TN, microvascular decompression, facial pain, stereotactic radiosurgery, and neuropathic pain.ConclusionThis is the first comprehensive scientific bibliometric analysis of the global research field on TN over the past 21 years, providing a meaningful reference for further exploration of topical issues and research trends in the field.