Network Visualization Research Articles

Mapping employability: a decade of trends and insights from higher education through bibliometric analysis (2014–2024)

Purpose This study aims to investigate the evolution of employability research within higher education from 2014 to 2024, using the career capital framework to provide a multifaceted perspective on employability. Design/methodology/approach The data set, comprising 468 documents from 1,170 authors, was analyzed using VOSviewer and the Bibliometric package in R, which enabled the visualization of bibliometric networks and the identification of significant research trends and influential publications. Findings Key findings emphasize the critical role of higher education in developing employability and the impact of various forms of graduate capital. The study reveals a shift from a narrow focus on job attainment to a broader perspective that includes long-term career sustainability and adaptability. Research limitations/implications Future research should explore contextual factors and develop holistic employability models. Interdisciplinary approaches and policy-informing studies are also recommended to enhance graduate employability in a dynamic global labor market. This research contributes to a deeper understanding of employability, supporting the development of effective strategies for preparing individuals for successful and adaptable careers. Originality/value This study integrates the component of graduate capital with employability, providing a more sophisticated comprehension of employability that surpasses conventional measurements. Having this viewpoint is crucial for higher education institutions to provide graduates with the necessary skills for long-term professional success and flexibility in a continuously changing job market. Furthermore, it provides valuable insights for the creation of educational programs and career services that can effectively equip students with the necessary skills and knowledge to navigate the intricacies of the contemporary labor market.

Metadag: a web tool to generate and analyse metabolic networks

BackgroundMetaDAG is a web-based tool developed to address challenges posed by big data from omics technologies, particularly in metabolic network reconstruction and analysis. The tool is capable of constructing metabolic networks for specific organisms, sets of organisms, reactions, enzymes, or KEGG Orthology (KO) identifiers. By retrieving data from the KEGG database, MetaDAG helps users visualize and analyze complex metabolic interactions efficiently.ResultsMetaDAG computes two models: a reaction graph and a metabolic directed acyclic graph (m-DAG). The reaction graph represents reactions as nodes and metabolite flow between them as edges. The m-DAG simplifies the reaction graph by collapsing strongly connected components, significantly reducing the number of nodes while maintaining connectivity. MetaDAG can generate metabolic networks from various inputs, including KEGG organisms or custom data (e.g., reactions, enzymes, KOs). The tool displays these models on an interactive web page and provides downloadable files, including network visualizations. MetaDAG was tested using two datasets. In an eukaryotic analysis, it successfully classified organisms from the KEGG database at the kingdom and phylum levels. In a microbiome study, MetaDAG accurately distinguished between Western and Korean diets and categorized individuals by weight loss outcomes based on dietary interventions.ConclusionMetaDAG offers an effective and versatile solution for metabolic network reconstruction from diverse data sources, enabling large-scale biological comparisons. Its ability to generate synthetic metabolisms and its broad application, from taxonomy classification to diet analysis, make it a valuable tool for biological research. MetaDAG is available online, with user support provided via a comprehensive guide. MetaDAG: https://bioinfo.uib.es/metadag/ User guide: https://biocom-uib.github.io/MetaDag/

Mapping the Research Landscape: A Comprehensive Bibliometric Review of Global Warming and Human Health

ABSTRACTHuman health is increasingly threatened by global warming, necessitating a thorough understanding of research progress in this critical area to inform future studies. The data were analysed using Microsoft Excel 2021, and visualisations were created with GraphPad, VOSviewer and R‐Studio (Bibliometrix). These tools were used to generate graphs and network visualisations illustrating author and country collaborations, journal article distributions, hotspot clustering and future trend predictions. Our analysis revealed a substantial increase in publications in recent years, with intensified research and collaboration observed across Asia, Europe, North America and Oceania, particularly in the United States. Various high‐impact journals have made meaningful contributions to raising awareness in this field, emphasises the multifaceted impacts of global warming on public health and societal activities, while also exploring adaptive measures being implemented in response to these changes. As the world continues to grapple with the global pandemic, further research is likely to spotlight related issues, with heightened interest anticipated. The evidence of global warming's impact on human health is becoming increasingly evident, underscoring the need for global cooperation to mitigate its effects and promote public health. This study provides a foundation for researchers and policymakers, highlighting the significance of addressing global warming's implications for human well‐being. By fostering international collaboration, we can collectively strive toward sustainable strategies to combat global warming and safeguard public health.

One Health preparedness and response for mosquito-borne viruses: a stakeholder- and social network-analysis in the Netherlands

BackgroundThe emergence of mosquito-borne viruses (MBVs) in Europe emphasizes the need for preparedness and response plans. This requires knowledge integration and collaboration across the human, animal, vector, and environmental health domains, aligning with the One Health approach. Despite the importance of a One Health approach, engaging stakeholders from each domain remains challenging. This study aims to identify stakeholders in the field of preparedness and response to MBVs in the Netherlands and map collaborations, knowledge- and information-sharing between these stakeholders, their domains and governance levels. In addition, we aim to identify bottlenecks in these networks and uncover underlying reasons.MethodsThis study combined stakeholder- and social network analysis. Stakeholders were identified through document analysis and snowballing. Semi-structured interviews were conducted with eligible stakeholders. Stakeholders’ collaborations, dependencies, and their roles in MBV preparedness and response were discussed. Interviewees not currently active in MBV policy were given the opportunity to share their experiences regarding ‘zoonotic infectious diseases’ or ‘healthy living environments’. Interview transcripts were coded to identify collaborations and information- and knowledge sharing between stakeholders. Stakeholders were categorized into domains (animal, vector, human, environment, other) and governance levels (international, national, regional, local, other). Networks were visualized and analysed using Cytoscape and R.ResultsStakeholder analysis identified 87 stakeholders who influence or are (likely to be) influenced by MBV preparedness and response, of whom 47 were identified as having an active role in the MBV interaction network. Network visualisation unveiled 153 connections among these 47 stakeholders, encompassing all domains and governance levels but showed underrepresentation of regional, local and environmental stakeholders. Transcript analysis revealed low urgency for MBVs among these stakeholders as an underlying reason for their underrepresentation in the MBV interaction network. Analysis and visualisation of the networks for the other two themes (“healthy living environment” and “(zoonotic) infectious diseases”) did show multiple connections with environmental and regional/local stakeholders.ConclusionsThe underrepresentation of the environment domain, regional and local stakeholders in the MBV preparedness and response network underlines the remaining challenge of including all relevant stakeholders. We recommend utilising existing collaborations, identified in this study, and central stakeholders to overcome these bottlenecks.

AOP-networkFinder — A versatile tool for the reconstruction and visualization of adverse Outcome Pathway networks from AOP-Wiki

Abstract Motivation The AOP-Wiki, a knowledge database for Adverse Outcome Pathways (AOPs), requires an efficient way to present an overview of its content for the reconstruction of networks by experts in a given domain. We have developed the AOP-networkFinder, a user-friendly tool that retrieves AOPs of interest, allows network generation and cleaning, and finally visualizes networks built around the retrieved AOPs. Our tool constructs AOP networks by connecting AOPs that use the same Key Events (KEs) in a versatile but controlled manner. Genes related to these KEs are also displayed. The constructed networks can then be exported as images or to Cytoscape for further fine-tuning and statistical analysis. Results The AOP-networkFinder allows users to comprehensively identify relationships between KEs and visualize the overall structure of an AOP both quickly and easily. This is immensely beneficial to researchers who need to understand the complex interplay between different KEs and the overall pathway they are studying and helps them to build further networks of interest while logging relevant information about changes within the network. These efforts are in line with the FAIR principles, which are crucial attributes for any developed databases and tools for optimizing (re)use in a dynamically changing landscape of AOP-Wiki. Availability and implementation The AOP-networkFinder is an open-source application and is available online at aop-networkfinder.no, in the ‘Computational Toxicology at Norwegian Institute of Public Health’ Zenodo community at DOI 10.5281/zenodo.11068434, in the GitHub repository at github.com/folkehelseinstituttet/AOPnetworkFinder_v1, as well as in a Docker image at hub.docker.com/r/nurre123/aop_network_finder. The software is available under the GNU Affero General Public License (AGPL), v3.0. The tool uses the AOP-Wiki SPARQL endpoint to retrieve AOP data.

Interdependency classification: A framework for infrastructure resilience

Abstract Critical Infrastructure Systems (CISs) provide essential services for nation-wide security, economy, and social well-being, and these systems are becoming increasingly interdependent to maintain those services. Recent and diverse disturbances worldwide have highlighted that interdependencies within CISs may increase the potential for cascading failures, amplifying the impacts of both large and small-scale disturbances into events of catastrophic proportions. The methodology involved conducting a literature search through scholarly databases and using a snowball approach to identify 12 relevant papers on infrastructure interdependencies. Thematic analysis was then applied to classify 50 interdependencies, which were synthesized into a unified classification system mapped to a foundational framework. The direct citation network visualization tool, Kumu, illustrated citation patterns and guided the analysis. Identifying and classifying various interdependencies, understanding their relationships, and assessing their role in CISs are crucial steps to prevent, mitigate, or manage unfavorable consequences and enhance system resilience. In this article, we compiled and identified classifications of infrastructure interdependencies and described a unified classification. To support the resilience of CISs in periods of stability and instability, infrastructure managers not only need consistent terminology but a shared understanding of interdependencies to ensure said interdependencies within and across CISs are appropriately accounted for throughout the life cycle of infrastructure, from early planning stages to management – reactive or proactive – for disturbances. These are critical steps toward understanding how CISs operate in concert so infrastructure managers may sense and anticipate potential disruptions, manage the impacts and consequences, and adapt to changing future conditions.

HapNetworkView: a tool for haplotype network exploration and visualization

BackgroundHaplotype networks are useful for investigating the genealogical relationships among haplotypes and have been extensively used in molecular evolution and population genetic studies. However, existing tools for visualizing haplotype networks lack comprehensive functionalities for data exploration and layout adjustments. Therefore, there is a need for a useful tool capable of constructing and visualizing haplotype networks, facilitating the exploration of data, particularly with datasets with large sample sizes.ResultsWe present HapNetworkView, a user-friendly tool that facilitates the construction and interactive visualization of haplotype networks, enabling users to explore haplotypes and mutation information effectively. HapNetworkView offers both automatic optimization and manual adjustment for haplotype network layouts. Additionally, HapNetworkView supports various input and output formats, as well as color customization.ConclusionsThese comprehensive functionalities collectively satisfy various needs of users in haplotype network analysis, making HapNetworkView a valuable tool.

Global research trends of BRUE (brief resolved unexplained event) or formerly ALTE (apparent life-threatening event): A comprehensive visualization and bibliometric analysis from 1988 to 2024.

This study aimed to conduct a comprehensive bibliometric analysis of the literature on Brief Resolved Unexplained Event (BRUE) and its predecessor, Apparent Life-Threatening Event (ALTE), from 1988 to 2024, in order to identify research trends, collaborative networks, and areas of focus in this field. We analyzed articles indexed in Scopus and Web of Science using various bibliometric indicators. The visualization of bibliometric networks was performed using VOSviewer and bibliometrix. Publication trends, citation analysis, co-authorship networks, and keyword co-occurrence were examined. A total of 270 articles were analyzed, of which 85.56% were research articles and 14.44% were review articles. The number of publications showed a significant increase over time (r=0.73, p<0.001). The United States emerged as the leading contributor with strong international collaborations. The most prolific journals were Pediatrics, Pediatric Emergency Care, and Journal of Pediatrics. Keyword analysis revealed a shift from terms associated with life-threatening events (e.g., SIDS, sleep apnea syndrome) to more specific terminology (BRUE) and methodological keywords over time. However, the 2016 redefinition of ALTE to BRUE did not result in a corresponding increase in publications. This bibliometric analysis provides valuable insights into the evolution and current state of BRUE/ALTE research. The findings highlight the field's progression toward more precise, evidence-based approaches. The identified research trends and gaps, particularly the limited studies from developing countries, offer direction for future research. These results can inform clinical practice, guide research priorities, and support the development of standardized guidelines for BRUE/ALTE management.

Enhanced multiscale human brain imaging by semi-supervised digital staining and serial sectioning optical coherence tomography

A major challenge in neuroscience is visualizing the structure of the human brain at different scales. Traditional histology reveals micro- and meso-scale brain features but suffers from staining variability, tissue damage, and distortion, which impedes accurate 3D reconstructions. The emerging label-free serial sectioning optical coherence tomography (S-OCT) technique offers uniform 3D imaging capability across samples but has poor histological interpretability despite its sensitivity to cortical features. Here, we present a novel 3D imaging framework that combines S-OCT with a deep-learning digital staining (DS) model. This enhanced imaging modality integrates high-throughput 3D imaging, low sample variability and high interpretability, making it suitable for 3D histology studies. We develop a novel semi-supervised learning technique to facilitate DS model training on weakly paired images for translating S-OCT to Gallyas silver staining. We demonstrate DS on various human cerebral cortex samples, achieving consistent staining quality and enhancing contrast across cortical layer boundaries. Additionally, we show that DS preserves geometry in 3D on cubic-centimeter tissue blocks, allowing for visualization of meso-scale vessel networks in the white matter. We believe that our technique has the potential for high-throughput, multiscale imaging of brain tissues and may facilitate studies of brain structures.

BIBLIOMETRIC ANALYSIS OF RISK TOLERANCE: GLOBAL COLLABORATION AND THEMATIC EVOLUTION

This study aims to analyze the development of research on risk tolerance over the past two decades, focusing on collaborative networks among authors and countries, thematic evolution, and new research opportunities. The method used is bibliometric analysis based on R software and VOS Viewer. The research population includes 833 articles related to risk tolerance identified from the Scopus database. The study was conducted through network visualization, thematic clustering, and thematic evolution mapping. The results show that publications on risk tolerance have increased by 15% annually, with the United States as the primary contributor. The main recurring themes include risk assessment, decision-making, and financial risk tolerance. However, there is a gap in integrating the risk tolerance theme with broader concepts such as financial literacy. The analysis also indicates increased international collaboration, particularly in North America, Europe, and Asia, but with limited cooperation in Latin America and Africa. This study recommends further exploration of the relationship between risk tolerance, financial literacy, and technology-based decision-making. Additionally, it suggests enhancing cross-regional collaborations to broaden the scope and impact of research in this field.

Academic Research Trend Analysis in the Past Twenty-five Years of Electric Vehicle Industry by Network Visualisation

The study investigates the visualised network regarding the research focuses and trends of the electric vehicle industry by VOSviewer and Gephi software. A co-occurrence network was constructed based on cleaned data, with a threshold of five and 1000 selected keywords. There are three types of visualisations presented in coloured clusters, overlay and density. The VOSviewer illustrates a network with 991 nodes, 242,749 edges, and a total link strength of 1,884,874. Although three visualisations represent the same network, each contains a unique perspective of information, which is the categorisation of research topics, the time arrangement of the studies over the years, and the influential power. The analysis is based on the network graph, structure, keywords position and parameters. The study finds that research areas of the EV industry are significantly dense and overlapping. The sector is inferred to focus more on innovative EV technologies, which will guide researchers and stakeholders in exploring the field more.

AUTOGRAPH: Chemical Reaction Networks in 3D.

Understanding and analyzing large-scale reaction networks is a fundamental challenge due to their complexity and size, often beyond human comprehension. In this paper, we introduce AUTOGRAPH, the first web-based tool designed for the interactive three-dimensional (3D) visualization and construction of reaction networks. AUTOGRAPH emphasizes ease of use, allowing users to intuitively build, modify, and explore individual reaction networks in real time. The platform supports a wide range of formats, including CHEMKIN, ensuring compatibility and seamless integration with existing data. Key features of AUTOGRAPH include advanced 3D visualization techniques combined with a fast force-directed algorithm, shortest-path searching, and filtering, facilitating the in-depth exploration of reaction networks. By providing detailed and interactive visualizations, our tool enhances users' ability to comprehend, analyze, and present complex reaction networks, making it a valuable resource for researchers dealing with intricate chemical systems.

The Atlas of Protein-Protein Interactions in Cancer (APPIC)-a webtool to visualize and analyze cancer subtypes.

Cancer is a complex disease with heterogeneous mutational and gene expression patterns. Subgroups of patients who share a phenotype might share a specific genetic architecture including protein-protein interactions (PPIs). We developed the Atlas of Protein-Protein Interactions in Cancer (APPIC), an interactive webtool that provides PPI subnetworks of 10 cancer types and their subtypes shared by cohorts of patients. To achieve this, we analyzed publicly available RNA sequencing data from patients and identified PPIs specific to 26 distinct cancer subtypes. APPIC compiles biological and clinical information from various databases, including the Human Protein Atlas, Hugo Gene Nomenclature Committee, g:Profiler, cBioPortal and Clue.io. The user-friendly interface allows for both 2D and 3D PPI network visualizations, enhancing the usability and interpretability of complex data. For advanced users seeking greater customization, APPIC conveniently provides all output files for further analysis and visualization on other platforms or tools. By offering comprehensive insights into PPIs and their role in cancer, APPIC aims to support the discovery of tumor subtype-specific novel targeted therapeutics and drug repurposing. APPIC is freely available at https://appic.brown.edu.

Training activity in improving emergency skill for healthcare workers: a systematic review assisted with Rstudio

Background: This study analyzed an emergency situation that requires immediate action by a doctor. Emergencies can occur anywhere, such as in hospitals, ambulances, even on the battlefield. Emergencies require doctors to have appropriate competence in order to treat patients quickly and appropriately. Apart from that, patient care is often found to be less than optimal. To deal with this problem, action is certainly needed so that patients can get maximum treatment. Method: This research is a literature review from the results of Web of Science, SCOPUS, and Google Scholar searches on research studies on emergency care published from 2021 to 2024. The data source was obtained from the Scopus database. The collected data is then exported to a text file in CSV form for further analysis with the help of the Rstudio Package, which includes networking and Biblioshiny visualization. Results: The results showed that many literatures explain the solution to overcoming problems in dealing with emergencies is by training, hands-on practice, and the application of various learning models to prepare nursing students to deal with patients in emergencies. for example, training to deal with patients with chest pain, heart attacks, and treating patients who are in conflict areas. learning methods that can be applied in learning include Basic Emergency Cource (BEC) which can increase student knowledge and confidence when managing emergency conditions, and Evidence-based practice can increase student self-efficacy, attitudes, and behavior in dealing with emergency patients.

Study on mechanism of Spatholobi Caulis in the treatment of the hand-foot skin reaction induced by targeted drug therapy based on network pharmacology and molecular docking: An observational study.

Based on network pharmacology and molecular docking methods, this study explored its active compounds and confirmed its potential mechanism of action against Hand-foot skin reaction induced by tumor-targeted drugs. Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform and UniProt Database were used to obtain the active ingredients and target proteins of Spatholobi Caulis. All hand-foot skin reaction (HFSR)-related targets were obtained with the help of the Human Gene Database, Online Mendelian Inheritance in Humans (OMIM), DisGeNET and DrugBank databases. Cytoscape 3.7.1 software was used to construct the active ingredient-target visualization network of Spatholobi Caulis, and the common target network of Spatholobi Caulis and HFSR. And through the BisoGenet plug-in in Cytoscape, PPI network topology analysis was performed. The Metescape database and online mapping tool platform were used for Gene Ontology (GO) function and Kyoto Encyclopedia of Genes Genomes (KEGG) pathway enrichment analysis to identify the key pathways of Spatholobi Caulis. Finally, Autodock Vina software and PyMol 2.5 software were used for molecular docking verification. There were 24 active components of Spatholobi Caulis and 244 target genes, 1635 disease-related target genes, 51 common target genes of Spatholobi Caulis and Hand-foot skin reaction, and key targets included NTRK1, epidermal growth factor receptor (EGFR), APP, TP53, HSP90AB1, HSP90AA, CUL3, etc. GO functional analysis involved a total of 66 molecular functions, 39 cellular components, and 817 biological processes. KEGG pathway analysis found 154 related signaling pathways, mainly enriched in Pathways in cancer, Human cytomegalovirus infection, Kaposi arcoma-associated herpesvirus infection, panic cancer, EGFR tyrosine kinase inhibitor resistance, P13K-Akt signaling pathway, Proteoglycans in cancer, HIF-1 signaling pathway and Ras signaling pathway, etc. Molecular docking results showed that luteolin, the active component of Spatholobi Caulis, had a high affinity with EGFR. Medicagol, the active components of Spatholobi Caulis, is proved in the Hand-foot skin reaction induced by lung cancer targeted therapy by regulating multiple signaling pathways through EGFR. It is confirmed that the treatment of Hand-foot skin reaction has the characteristics of multi-component, multi-target and multi-pathway regulation.

Digital Financial Innovation In SMEs: A Bibliometric Approach

In the era of digitalization that continues to develop from 4.0 and will enter the era of 5.0. Conditions like this direct the trend of digital transformation for the implementation of SMEs. Studies related to financial management innovation in SMEs are needed to improve adaptation in the digital era. Many studies are needed to improve the development of science related to financial management in improving the ability to understand, predict and manage the implementation of digital financial innovation. To review the literature review, articles were collected from well-known publishers such as Elsevier, Springer, Emerald, Taylor &amp; Francis, Wiley Online Library, proquest, ebscohost, and sage. Selected articles related to the theme of digital financial innovation in SME companies were collected as many as 953 using the Publish or Perish application. This number consists of articles published from 2005 to 2024. Mapping of the articles was carried out using bibliometric methods and scientific visualization using the VOSviewer application. Network visualization analysis shows that Fintech and Blockchain technology have the strongest total link strength. Overlay visualization analysis shows that the theme related to Digital Financial Innovation in SMEs is a new theme in the development of research trends. Density visualization analysis shows that themes related to Blockchain technology, and Fintech are frequently discussed themes. On the other hand, Financial inclusion, SME, financial literacy and digital innovation have less intensity.

Does This Have a Particular Meaning? Interactive Pattern Explanation for Network Visualizations.

This paper presents an interactive technique to explain visual patterns in network visualizations to analysts who do not understand these visualizations and who are learning to read them. Learning a visualization requires mastering its visual grammar and decoding information presented through visual marks, graphical encodings, and spatial configurations. To help people learn network visualization designs and extract meaningful information, we introduce the concept of interactive pattern explanation that allows viewers to select an arbitrary area in a visualization, then automatically mines the underlying data patterns, and explains both visual and data patterns present in the viewer's selection. In a qualitative and a quantitative user study with a total of 32 participants, we compare interactive pattern explanations to textual-only and visual-only (cheatsheets) explanations. Our results show that interactive explanations increase learning of i) unfamiliar visualizations, ii) patterns in network science, and iii) the respective network terminology.

Bibliometric Analysis and ChatGPT-Assisted Identification of Key Strategies for Improving Primary Maternity Care Based on a Decade of Collective Research.

Maternity care within primary health facility settings is critical for reducing maternal and neonatal mortality in Indonesia. The aim of this study was to analyze research trends over the past decade to identify key strategies for improving maternity care in primary health care facilities in Indonesia. A bibliometric analysis was conducted using data from the Scopus database to map the research landscape and identify latent research topics in maternal health care. The analysis included keyword co-occurrence and network visualization, with assistance from ChatGPT-4.0 for enhanced identification and categorization of keywords. The identified research trends were used as surrogate variables representing the main concerns among researchers, experts, and funders. These variables were used to build strategies, which were then analyzed using SWOT (Strengths, Weaknesses, Opportunities, and Threats) by reflecting on the Indonesian context. The results revealed that key topics in maternity care included midwifery roles, pandemic resilience, and telemedicine. Based on SWOT analysis, most of the constructed strategies were found to have high external opportunities but low internal capabilities, indicating the need to strengthen internal resources. In conclusion, Indonesia must enhance its internal capabilities, particularly human resources and infrastructure, to effectively utilize external opportunities and improve maternal health outcomes.

PhosNetVis: A web-based tool for fast kinase-substrate enrichment analysis and interactive 2D/3D network visualizations of phosphoproteomics data

PhosNetVis: A web-based tool for fast kinase-substrate enrichment analysis and interactive 2D/3D network visualizations of phosphoproteomics data

Research focus and theme evolution on enhanced external counterpulsation: A bibliometric analysis.

The study delved into the identification of key research areas and evolving trends within the domain of Enhanced External Counterpulsation, aiming to gain comprehensive insights into the subject matter. Utilizing the sophisticated search parameter of 'topic' (TS) on the Web of Science (WoS) database, the necessary information was retrieved. This research employed an array of tools for effective data extraction, analysis, and visualization, which included Microsoft Excel for tabular management, HistCite Pro for citation analysis, GunnMap for geographical mapping, BibExcel for bibliometric assessments, and VOSviewer for network visualization purposes. From its establishment up until March 31, 2024 a total of 535 entries were recorded in the WoS database, with 491 of these relevant to the specified subject matter. The USA was the most prolific country, and China ranked second. Sun Yat Sen University was the most productive institution, which was from China. And 80% of the top 10 institutions were from the USA. A keyword co-occurrence analysis was conducted, revealing four distinct research foci. And they were the application of EECP in cardiovascular disease, the main indications of EECP, the mechanism of EECP and the therapeutic effect of EECP, respectively. Researchers paid the most attention to the application of EECP on the cardiac cardiovascular system. Professor Lawson WE, Hui JCK and Kennard ED were the top three prolific authors. Lawson WE, Henry TD, Braith RW and Zheng ZS were identified as the core authors in the author co-citation network analysis. A comprehensive analysis was conducted on the literature surrounding improved enhanced external counterpulsation in this investigation, which can help researchers understand the theme trend better and grasp the research gap, to carry out further research and promote the progress of the topic.