Bibliometric analysis of research trends on the epiretinal membrane since 2000.

Alzheimer’s disease (AD) is a neurodegenerative disorder that severely impacts cognitive function, posing significant physical and psychological burdens on patients and substantial economic challenges to families and society, particularly in aging populations where its prevalence is rising. Current diagnostic and therapeutic strategies, including pharmacological treatments and non-pharmacological interventions, exhibit considerable limitations in early diagnosis, etiological treatment, and disease management. This study aims to investigate the application of artificial intelligence (AI) in the early diagnosis and progression monitoring of AD through a bibliometric analysis of relevant literature. A systematic search in the Web of Science Core Collection identified 530 publications related to AI and AD, consisting of 361 original research articles and 169 review articles, with a notable increase in annual publication rates, particularly between 2019 and 2024. The United States and China emerged as leading contributors, emphasizing the importance of international collaboration. Institutional analysis revealed that Harvard University and Indiana University System are at the forefront, highlighting the role of academic institutions in fostering interdisciplinary research. Furthermore, the Journal of Alzheimer’s Disease was identified as the most influential publication outlet. Key highly cited papers provided essential theoretical foundations for ongoing research. This study underscores the growing relevance of AI in AD research and suggests promising avenues for future investigations, particularly in enhancing diagnostic accuracy and therapeutic strategies through advanced data analytics and machine learning techniques.

China is a country with high incidence of esophageal cancer. Advanced esophageal cancer not only brings serious threat to the health of patients, but also brings heavy economic burden to their families and society. Early diagnosis and treatment of esophageal cancer are always the hot spot in clinical research, and gastroscopy screening is the key point. The development of artificial intelligence is expected to provide new mean for early diagnosis and treatment of esophageal cancer in the aspects of endoscopy procedure and quality control.Through a brief overview of the concept and development of artificial intelligence in endoscopic diagnosis of superficial esophageal cancer, this study summarizes and reviews the research progress of artificial intelligence in the diagnosis of superficial esophageal carcinoma, and illustrates the importance of its application. This study also discusses the main problems and difficulties of artificial intelligence in the endoscopic diagnosis of esophageal carcinoma. It prospects the application of artificial intelligence in endoscopic esophageal diagnosis in the future.

Chronic obstructive pulmonary disease (COPD) is increasingly recognized as a disorder influenced by the respiratory microbiota. Microbial dysbiosis has been linked to disease progression, inflammation, and clinical outcomes. However, a comprehensive overview of the global research landscape and evolving themes in this field is still lacking. Publications on COPD and respiratory microbiota were retrieved from the Web of Science Core Collection (WoSCC) and Scopus databases. Bibliometric analyses, including publication trends, co-authorship networks, keyword co-occurrence, citation bursts, and thematic evolution, were conducted using VOSviewer, CiteSpace, and the bibliometrix package in R. Between 2001 and 2025, 296 publications were identified in WoSCC and 433 in Scopus, reflecting a sustained growth in research output. Keyword co-occurrence and clustering analyses revealed three main research hotspots: (1) respiratory microbiota composition and dynamics, (2) pathogen colonization and inflammation-related processes, and (3) clinically relevant outcomes. Citation burst and thematic evolution analyses demonstrated a clear temporal shift from pathogen-centered studies toward microbiota-based, dynamic, and clinically oriented research paradigms. International collaboration is increasingly prominent, with China, the USA, and the UK leading in productivity and citation impact. This bibliometric study systematically delineates the intellectual structure and evolving trends of COPD-related respiratory microbiota research. Our findings highlight the maturation of the field, reveal emerging research directions such as multi-omics integration and gut-lung axis interactions, and provide a quantitative reference for guiding future translational and microbiota-focused studies in COPD.

Ferroptosis, an iron-dependent regulated cell death mechanism, has recently gained attention for its crucial role in tumor progression and immune regulation. Gastric cancer (GC), one of the most common and deadly malignancies worldwide, remains a major clinical challenge. This study aims to systematically analyze the global research landscape, hotspots, and trends of ferroptosis in gastric cancer from 2017 to 2025, with a focus on its immunological implications. Publications related to ferroptosis and gastric cancer published between January 1, 2017 and April 22, 2025 were retrieved from the Web of Science Core Collection (WoSCC) and Scopus databases (n = 974). Bibliometric and visualization analyses were performed using R software (bibliometrix package), VOSviewer, and CiteSpace to explore publication trends, collaboration patterns, keyword co-occurrence, and thematic evolution. Research output showed a continuous upward trend, with China leading in publication volume, followed by the United States, Japan, Canada, and South Korea. Frontiers in Pharmacology and Frontiers in Oncology were the most productive journals, while Cell and Nature were the most frequently cited. The most prominent themes included "immune checkpoint," "tumor immune microenvironment," "ferroptosis mechanisms," "drug resistance," and "non-coding RNAs." Notably, the STAT3-ferroptosis axis and immune pathways were identified as key translational targets. Ferroptosis has become an important research frontier in gastric cancer and is increasingly recognized as a promising therapeutic strategy to modulate the tumor immune microenvironment and enhance immunotherapy efficacy. This study provides a comprehensive overview of the global research landscape, offering valuable guidance for future studies in cancer immunology and ferroptosis-based therapy.

Heparin-binding protein (HBP), also known as azurocidin, is a neutrophil-derived mediator that modulates vascular permeability and inflammatory responses and has been actively studied in relation to infection and sepsis. Despite significant growth in research on HBP over the last few decades, there has been a lack of an overall picture of research trends worldwide, collaboration networks, and the evolution of themes. This paper aims to trace the knowledge base and evolution of HBP-related research on infection and sepsis using bibliometric methods. The articles were obtained from the Web of Science Core Collection and the Scopus database, which cover publications from 1981 to 2025. Following duplication and screening, 1,599 publications with full bibliographic information were included. Collaboration networks, patterns of keyword co-occurrence, and research hotspots were analyzed using CiteSpace and VOSviewer, whereas descriptive statistics were conducted in Microsoft Excel. The publications and citations alluding to HBP continued to grow, especially since 2010. Sweden, the United States, and the People's Republic of China were the most contributing countries, and the networks of international collaboration focused on Swedish research groups. The most fruitful institutions were Lund University and Karolinska Institutet. Keyword co-occurrence and burst analysis revealed a transition from early molecular/mechanistic research to more clinically focused research, especially those investigating the diagnostic and prognostic capabilities of HBP in organ dysfunction and sepsis. The core journals were primarily in the areas of immunology, critical care, and infectious disease. Overall, HBP research has progressed from molecular discovery toward clinically oriented biomarker evaluation, although large-scale clinical implementation remains limited. Nevertheless, to date, HBP has not been part of standard clinical practice for diagnosing or treating sepsis. Recent research focuses on biomarker validation and prognostic evaluation, arguing that, before any wide-scale clinical use, a biomarker must undergo large-scale validation.

Recent years have witnessed rapid progress in mitochondrial transplantation (MT) as a novel strategy for restoring mitochondrial function in diverse pathological conditions, including somatic mitochondrial transfer and reproductive mitochondrial replacement therapy. With its expanding applications in regenerative medicine and disease modeling, systematic quantitative evaluation of the global MT research landscape remains limited. To address this gap, we performed a bibliometric analysis of publications indexed in the Web of Science Core Collection from 1996 to 2024, with cross-database validation using Scopus. CiteSpace, VOSviewer, and the R package bibliometrix were applied to assess publication trends, collaboration networks, co-citation patterns, and keyword co-occurrence. In total, 1104 articles and reviews were included. The results revealed rapid growth in MT-related research, with the United States and China as leading contributors. Mitochondrion emerged as the most influential journal, while Yamada Y, Harashima H, and McCully JD were recognized as key authors. High-frequency keywords highlighted major themes including mitochondrial transfer, mesenchymal stem cells, and ischemia-reperfusion injury. Emerging terms such as extracellular vesicles, tunneling nanotubes, and advanced delivery systems, particularly the MITO-Porter platform, reflected current research frontiers. Overall, this study provides a comprehensive overview of global research trends and evolving directions in mitochondrial transplantation.

Robot-assisted breast reconstructive surgery has emerged as an evolving application of minimally invasive and robotic surgery in breast and reconstructive practice. However, its global research landscape, collaborative patterns, intellectual structure, and thematic evolution have not been systematically characterised. This study aimed to map the development, research hotspots, and emerging trends in robot-assisted breast reconstructive surgery through bibliometric and visualisation analyses, while recognising its close clinical overlap with robotic nipple-sparing mastectomy and immediate reconstruction. Publications on robot-assisted breast reconstructive surgery published between 1 January 2005 and 31 December 2025 were retrieved from the Web of Science Core Collection (WoSCC). A relatively sensitive retrieval strategy was used first, followed by manual screening, to capture reconstructive literature developing in close association with robotic nipple-sparing mastectomy and related oncologic-reconstructive procedures. After screening, 218 publications were included. Bibliometric and visualisation analyses were performed using Bibliometrix, CiteSpace, VOSviewer, and Scimago Graphica to evaluate annual publication trends, contributions by countries, institutions, authors, and journals, as well as co-citation networks, keyword co-occurrence, clustering, burst detection, and thematic evolution. A total of 218 publications, including 164 original articles and 54 reviews, were identified. Annual output remained limited before 2018 but increased markedly thereafter. China, Korea, and the United States were the most active contributors, while Changhua Christian Hospital and Yonsei University were the leading institutions. Plastic and Reconstructive Surgery was the most productive and most locally cited journal. Lee J and Park HS were the most productive authors, whereas Lai HW, Selber JC, Toesca A, and Sarfati B emerged as key collaborative and intellectual hubs in the field. Major research themes included oncologic safety, nipple-sparing mastectomy, immediate breast reconstruction, flap reconstruction, donor-site morbidity, free flap, and robotic microsurgery. Trend analyses indicated a shift from early feasibility-focused studies toward more specialised concerns involving oncologic safety, advanced autologous reconstruction, and microsurgical refinement. Research on robot-assisted breast reconstructive surgery has expanded rapidly in recent years and is increasingly concentrated in a limited number of leading countries, institutions, authors, and journals. The field appears to have evolved from early technical feasibility studies toward a more specialised and clinically connected stage of scholarly attention, with growing emphasis on oncologic safety, nipple-sparing mastectomy, immediate reconstruction, donor-site optimisation, and advanced microsurgical or autologous applications. This study provides a structured overview of the global development and thematic evolution of robot-assisted breast reconstructive surgery and may serve as a useful reference for future clinical research and academic collaboration.

Project management has become increasingly critical in automotive manufacturing enterprises due to rising product complexity, digital transformation, and global supply chain uncertainty. Although a growing body of research has examined project management practices in the automotive sector, existing studies remain fragmented across multiple disciplines, and a systematic synthesis of the knowledge structure is still lacking. To address this gap, this study conducts a comprehensive bibliometric review of project management research in automotive manufacturing enterprises based on 247 publications retrieved from the Web of Science Core Collection. Using performance analysis and science mapping techniques, this study examines publication trends, country collaboration patterns, influential journals and authors, and keyword co-occurrence and clustering structures. The results reveal a sustained growth in research output since the mid-2010s, accompanied by an increasingly international and polycentric collaboration network dominated by Germany, the United States, and China. The cited journal and author analyses indicate that the intellectual foundation of the field is highly interdisciplinary, integrating project management, operations management, production economics, and supply chain research. Keyword co-occurrence and clustering analyses further demonstrate a clear thematic evolution from early emphases on risk management and decision-making models toward more integrated perspectives encompassing supply chain coordination, dynamic capabilities, sustainability, and electric vehicle–related issues. By systematically mapping the intellectual structure and thematic evolution of the literature, this study contributes to a clearer understanding of how project management research in automotive manufacturing enterprises has developed over time. The findings provide valuable insights for both scholars and practitioners and highlight promising directions for future research in the context of an increasingly complex and dynamic automotive industry.

Aims: Three-dimensional (3D) printing of zirconia is an emerging domain in digital dentistry; however, its global research landscape, collaboration structure, and thematic focus have not been comprehensively mapped. The aim of this study was to characterize scientific output, collaboration patterns, citation impact, and major research themes in publications on 3D-printed zirconia in dentistry.Methods: A Web of Science Core Collection (WoS-CC) Topic Search was conducted in December 2025 using terms related to zirconia, additive manufacturing/3D printing, and dental applications. Of 584 retrieved records, 185 eligible articles on 3D-printed zirconia for dental use (2009–2025) were included. Descriptive indicators were calculated (annual production, journals, countries, institutions, authors, and citations). Co-authorship and keyword co-occurrence networks were generated with VOSviewer to visualize collaboration and identify thematic clusters.Results: Publication activity increased sharply after 2019, with 128/185 publications (69.2%) published in 2023–2025. Most documents were original research articles (n=159) or reviews (n=26); no case reports were identified in WoS-CC. The 185 articles involved 730 authors from 38 countries and were published in 48 journals. China and the United States were leading contributors. Network analyses identified three interconnected themes: digital/additive manufacturing workflows, implantprosthodontic applications, and biomechanical or accuracy-based evaluation. Evidence was predominantly in vitro and laboratory-based, with limited clinical data.Conclusion: Research on 3D-printed zirconia in dentistry is rapidly expanding but concentrated in a small set of countries, institutions, and journals. Future studies should prioritize clinical investigations and standardized reporting of printing and post-processing parameters to support translation into predictable outcomes.

Irisin, a myokine induced by exercise, is a key regulator of metabolic processes and cardiovascular health, has emerged as a potential biomarker and therapeutic target in cardiovascular disease. However, the global research landscape on this topic has not been systematically mapped. The aim of the study to provide a comprehensive bibliometric analysis of irisin-related cardiovascular research published between 2012 and 2025. Publications indexed in the Web of Science Core Collection were analysed using VOSviewer. Annual output, country- and institution-level productivity, co-authorship patterns, document citations, and author keyword co-occurrence were assessed. Annual output revealed a three-phase trajectory: rapid emergence (2012–2015), steady expansion (2016–2021), and recent volatility without contraction (2022–2025). China was the most prolific contributor (194 publications), followed by the United States (55), Türkiye (40) and Italy (34). Firat University (Türkiye) and Southwest Medical University (China) were the most productive institutions, while Harvard University (USA) achieved the highest citation impact. Co-authorship analyses showed China and the United States as global anchors, though collaboration remained regionally clustered. Highly cited works by Pedersen (2012), Park (2013), and Perakakis (2017) served as conceptual anchors, with subsequent studies by Jedrychowski, Polyzos, Xiong, and Zhu consolidating the knowledge base. Keyword co-occurrence analysis positioned irisin as a central hub linking exercise physiology, metabolic disorders, and cardiovascular pathology, while overlay visualization showed a thematic shift from early mechanistic studies to cardiometabolic diseases and, most recently, cell-death pathways (pyroptosis, autophagy) and specialized clinical populations. In conclusion, irisin-related cardiovascular research has grown rapidly over the past decade, with China emerging as the dominant contributor and the United States maintaining strong collaborative reach. Thematic evolution reflects a trajectory from molecular mechanisms to clinical applications. Standardized methodologies and expanded multinational collaborations are needed to address existing gaps and advance irisin’s translational potential in cardiovascular medicine.

Machine learning based artificial intelligence technology for big data processing has shown great potential in predicting patients' conditions and aiding clinical decisions, and has been widely used in the development of clinical decision support systems in recent years. Sepsis is a life-threatening organ dysfunction caused by host response disorder caused by infection, and its early recognition and treatment can significantly improve the prognosis of patients. At present, there are many deficiencies in the clinical application of sequential organ failure assessment (SOFA), bedside quick sequential organ failure assessment (qSOFA), national early warning score (NEWS), inflammatory indicators, and novel biomarkers for evaluating sepsis. Artificial intelligence has promoted the development of critical care medicine because of its ability to rapidly process and analyze massive data of severe patients. This paper reviews the recent application of artificial intelligence in the early diagnosis and prediction of sepsis, in order to emphasize the importance and limitations of artificial intelligence in the diagnosis and prediction of sepsis.

ObjectiveDry needling (DN) has been shown to exert beneficial effects in pain management. However, a comprehensive bibliometric analysis specifically examining the relationship between DN and pain has not yet been conducted. This study aims to systematically evaluate the global research landscape and emerging trends in the field of “dry needling and pain” from 2006 to 2025 using bibliometric methods, thereby providing a quantitative foundation and forward-looking guidance for future basic and clinical research.MethodsA bibliometric analysis was conducted using literature published between 2006 and 2025, retrieved from the Web of Science Core Collection (WoSCC) and Scopus databases. Data were analyzed with Bibliometrix (R package), VOSviewer, and CiteSpace software.ResultsA total of 936 and 1,149 articles were retrieved from the WoSCC and Scopus databases, respectively. Over the past two decades, publication output in this field has steadily increased. The United States and Spain were the leading contributing countries, with Universidad Rey Juan Carlos in Spain serving as a central hub within the international collaboration network. Fernández-De-Las-Peñas C. was identified as the most prolific author. Journal analysis showed that the Journal of Bodywork and Movement Therapies published the most articles, whereas the Archives of Physical Medicine and Rehabilitation received the highest number of citations and acted as a key node in scholarly cooperation. Keyword co-occurrence and clustering analyses revealed four core research themes: evidence-based pain management, pathophysiological mechanisms of myofascial trigger points (MTrPs), clinical efficacy of DN for myofascial pain, and clinical trial design with outcome assessment. Current research hotspots focus on clinical effectiveness, mechanistic studies, refinement of trial methodologies, standardization of outcomes, and risk management in clinical practice.ConclusionThe application of DN in pain management has garnered increasing global attention and is poised to become a major focus within the field. This study provides a comprehensive overview of the current research status and emerging themes, offering valuable insights for future investigations.

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.

Lung ultrasound (LUS) is gaining recognition as an indispensable diagnostic tool in critical care. The study aimed to characterize the global research landscape and trend of LUS with quantification and visualization approaches. Documents related to LUS published between 2007 and 2023 were selected from the Web of Science Core Collection and identified. Visualization and statistical analysis were conducted with the VOSviewer 1.6.18, CiteSpace 5.7.R5, and Bibliometrix 4.1.0 Package, including analysis of the trend of global publications, prominent countries, active institutions, and funding agencies, key authors and journals, co-cited references, and keywords. A total of 3010 publications, including 2434 articles and 576 reviews, were retrieved. The output of LUS-related research has increased steadily over the years, especially after 2018. Italy (n=756; 25.12%) has shown the highest output, being the country with the highest total citations (23423 times). The most influential author was Gargani Luna with 52 documents, who worked at the Consiglio Nazionale delle Ricerche. Chest and Intensive Care Medicine with high citations and impact factor scores were the most influential journals. Besides "lung ultrasonography", the keywords developed included "coronavirus disease 2019 (COVID-19)", "acute respiratory distress syndrome", and "acute heart failure". Research output on LUS has increased steadily, especially after 2018. Italy and the United States are staying ahead in this field. Research collaboration still needs to be strengthened. This comprehensive analysis has presented the global research landscape and trends of LUS-related research, providing valuable information for researchers to pursue further exploration.

Craniopharyngioma is a congenital brain tumor with clinical characteristics of hypothalamic-pituitary dysfunction, increased intracranial pressure, and visual field disorder, among other injuries. Its clinical diagnosis mainly depends on radiological examinations (such as Computed Tomography, Magnetic Resonance Imaging). However, assessing numerous radiological images manually is a challenging task, and the experience of doctors has a great influence on the diagnosis result. The development of artificial intelligence has brought about a great transformation in the clinical diagnosis of craniopharyngioma. This study reviewed the application of artificial intelligence technology in the clinical diagnosis of craniopharyngioma from the aspects of differential classification, prediction of tissue invasion and gene mutation, prognosis prediction, and so on. Based on the reviews, the technical route of intelligent diagnosis based on the traditional machine learning model and deep learning model were further proposed. Additionally, in terms of the limitations and possibilities of the development of artificial intelligence in craniopharyngioma diagnosis, this study discussed the attentions required in future research, including few-shot learning, imbalanced data set, semi-supervised models, and multi-omics fusion.