Search Results (506)

Background/Objectives: The intersection of mental health and acute coronary syndromes has become an increasingly prominent area of cardiovascular and psychosomatic research, yet its temporal dynamics and intellectual structure remain incompletely characterized. Methods: This study analyzed 13,646 peer-reviewed documents spanning five decades, employing advanced changepoint detection (PELT) algorithms, network visualization (VOSviewer), and bibliometric performance metrics (Bibliometrix) to quantify the evolution of the mental health–ACS intersection. Results: Statistical analysis identified two robust inflection points at 1990 and 2005 that demarcate distinct developmental periods. The 1990 breakpoint marked an important transition, although additional metadata-completeness analysis indicated that part of the increase from 72 to 142 publications may reflect improved availability of non-title Topic-field metadata in WoSCC around 1990–1991. The 2005 breakpoint represented the most critical transition (Cohen’s d = 4.05, p < 0.000001), initiating exponential growth from 349 to over 600 annual publications by 2022 and coinciding with growing research attention to psychiatric comorbidity within ACS literature. Keyword co-occurrence networks revealed a shift in research focus: early publications predominantly addressed mental health as a psychological reaction to cardiac events, whereas more recent publications increasingly frame depression, anxiety, and PTSD alongside mechanistic constructs such as inflammatory pathways, autonomic dysfunction, and platelet reactivity. Although seminal intervention trials (i.e., ENRICHD, SADHART) established pharmacological safety and symptom improvement, keyword analyses indicate that following these trials, research attention increasingly shifted toward precision psychiatry concepts and mechanistic pathway elucidation. Conclusions: These findings provide a quantitative map of how publication activity at the mental health–ACS intersection has evolved, offering a structured basis for identifying under-researched areas and informing future research agendas. Full article

The demand for advanced detection methods and accurate staging remains a global challenge in cancer diagnosis. Even though traditional deep learning models in medical imaging achieve high precision, they suffer from limited explainability and multimodal reasoning due to their black-box nature, thereby limiting their clinical applicability. To address this gap, recent research has increasingly explored multimodal approaches that integrate visual and textual clinical data to enhance diagnostic accuracy and interpretability. This study presents a bibliometric analysis of 408 publications from 2021 to 2025, collected from Web of Science and Scopus, using VOSviewer and R-Bibliometrix to map citation networks, co-authorship, and keyword co-occurrences. The results reveal a rapid growth from 1 publication in 2021 to 269 in 2025, with significant contributions from leading countries and institutions. Thematic analysis indicates a shift from conventional convolutional approaches toward transformer-based and self-supervised methods, alongside increasing attention to multimodal learning in cancer imaging tasks such as breast, lung, and brain cancer analysis. Overall, this study provides a structured overview of the evolving research landscape, highlighting key trends, emerging themes, and research gaps to inform future developments in multimodal artificial intelligence for cancer diagnosis. Full article

The date palm (Phoenix dactylifera L.) is a significant perennial crop in arid and semi-arid regions. Understanding the evolution of research on this crop is vital for identifying major research trends, current challenges, and emerging areas for future agricultural innovation and sustainable crop management strategies. This study conducts a comprehensive scientometric analysis of 9062 scientific publications indexed in the Scopus database between 1837 and 2025, spanning nearly two centuries of research on date palm. Using bibliometric tools such as Bibliometrix and ScientoPy, the study examines patterns of scientific production, collaboration networks, institutional participation, thematic evolution, and emerging research trends. The results indicate a marked increase in scientific publications, especially after 2007, with Saudi Arabia, Egypt, and Iran among the most productive countries. The thematic structure of the literature shows a shift from early studies on diseases and oasis cultivation to recent research focusing on biomass valorization, activated carbon production, antioxidant properties, pest management with special emphasis on the red palm weevil (Rhynchophorus ferrugineus), mechanical properties of date palm fibers, and plant biotechnology on methods like micropropagation and somatic embryogenesis. Geographically, research activity is concentrated in the Middle East and North Africa, the primary palm-producing region, with Saudi Arabia leading in institutions, researchers, funding, and international collaborations in date palm research. Emerging trends indicate a rising interest in digital tools, particularly artificial intelligence and advanced analytical tools, which are increasingly being explored to improve crop management. Overall, these findings provide a structured overview of the historical development of date palm research and contribute to a deeper understanding of the evolution and organization of scientific knowledge in this field. Additionally, the identification of key research pathways and emerging trends offers valuable insights for guiding future agronomic innovation, supporting evidence-based crop management strategies, and promoting the sustainable development of date palm production systems. Full article

This study presents the first dedicated bibliometric analysis of artificial intelligence (AI) and deep learning applications in pediatric radiology and medical imaging, mapping the intellectual structure of a rapidly evolving field. A total of 2688 articles and conference proceedings published between 2005 and 2025 were retrieved from the Web of Science Core Collection and analyzed using Bibliometrix R and VOSviewer. The findings reveal exponential growth in publications, from 7 papers in 2005 to 559 in 2025, with journal articles dominating the corpus (85.9%). The most-cited contributions, led by Kermany et al. (2018) with 2886 citations, are predominantly technical feasibility studies rather than clinical outcome trials, indicating a field that has advanced methodologically but remains in early stages of clinical translation. Thematic mapping identifies convolutional neural networks, pneumonia, and transfer learning as Motor Themes representing methodological maturity in chest imaging, while neuroimaging and image segmentation clusters occupy Niche Themes, reflecting insular development with limited cross-field connectivity. Geographic analysis reveals concentrated co-authorship along US–China and US–Europe corridors, with African, Latin American, and Southeast Asian institutions largely absent from knowledge production networks. Eight of the ten most productive affiliations are North American, highlighting structural inequities that risk producing AI tools optimized for high-resource settings rather than the global pediatric population. This analysis provides an empirical foundation for reorienting the field toward clinical validation, geographic inclusion, and methodological integration across isolated research communities. Full article

This study investigates the relevant literature on applications of Artificial Intelligence (AI) for wood as a material using a systematic review and screening process. The Web of Science (WoS) database identified 50 peer-reviewed publications dealing with AI applications for wood as a material. Bibliometrix and VOSviewer software were used to evaluate publication trends, country contributions, keyword co-occurrences, and AI application areas. Based on these analyses, an annual growth rate of 23.28% between 2014 and 2025 (November) in publications published per year was measured and an average of 6.92 citations per publication was observed as of November 2025. Most notably, a considerable increase in AI-focused research after 2023 was identified. Before 2022, work done using AI tools (such as neural networks, deep learning, and others) did not necessarily use the term AI and hence were not found by our search. China, Canada, and Poland were the countries with the highest number of publications. The leading journals with publications on AI applications for wood as a material were Forests and Wood Material Science and Engineering. The most frequently occurring keywords in the publications reviewed were “AI,” “machine learning,” and “deep learning.” In general, according to the publications reviewed, AI applications for wooden materials improved productivity, material evaluation, and quality assurance. The findings highlighted the impact of AI on the sector and show that AI will change the industry. Full article

As global urbanization accelerates, biophilic urbanism has emerged as a key nature-based strategy for enhancing public health. While plants are critical active agents for psychological restoration, the specific pathways through which vegetation characteristics influence human–environment interactions remain fragmented. This knowledge gap hinders the evidence-based translation of biophilic principles into actionable urban design and governance. This study conducts a systematic bibliometric analysis of 443 peer-reviewed articles (2000–2025) at the intersection of restorative landscapes, urban settings, and plant-based interventions retrieved from the Web of Science Core Collection. Employing multiple visualization tools (VOSviewer, bibliometrix, and CiteSpace), we map publication trends, international collaborations, and thematic evolution. The results demonstrate a significant shift in the field, moving beyond the validation of foundational restorative theories (e.g., ART and SRT) to a more precise, implementation-oriented framework. This shift is characterized by the operationalization of vegetation attributes as controllable design variables, increasingly relating biophilic principles to broader nature-based solutions (NbS) agendas and evidence-informed urban governance. Thematic clustering analysis identified three core knowledge domains: (1) the role of plants as active exposure agents and behavioral mediators in psychological restoration; (2) the impact of specific plant characteristics—such as canopy structure, species diversity, and seasonal variation—on therapeutic outcomes; and (3) the integration of urban green spaces into broader governance frameworks to promote health equity and inclusive well-being. Our analysis highlights that plant-based interventions are evolving from aesthetic ornaments into precision design levers for fostering human–nature interactions. This study provides a science-based foundation for developing practical design guidelines and policy frameworks, shifting biophilic urbanism toward a robust governance strategy for creating equitable, restorative, and resilient cities. Full article

Artificial intelligence (AI) is increasingly embedded in banking risk management, yet academic research on this topic remains conceptually fragmented and dispersed across multiple disciplines. This study examines global publication trends and thematic structures related to AI applications in banking risk management through a bibliometric analysis of 83 peer-reviewed articles indexed in the Web of Science Core Collection for the period 2020–2024. The analysis was conducted using Bibliometrix (R-package, version 4.1), its web interface Biblioshiny (2024 release), to evaluate publication dynamics, citation performance, authorship patterns, and thematic clusters. Results show a substantial rise in scientific interest, with annual publication growth of 41.4% and international co-authorship reaching 30%. Five major thematic clusters were identified, including AI-enabled credit risk assessment, fraud detection, operational and cyber-risk mitigation, FinTech adoption, and regulatory compliance. Approximately 30% of the articles appeared in the top ten journals publishing on the topic, and the dataset recorded more than 3800 cited references. The findings indicate that AI contributes to enhanced predictive accuracy, real-time anomaly detection, and supervisory efficiency in banking risk management, while persistent challenges relate to model transparency, data quality, and regulatory adaptation. This study offers a systematic, data-driven understanding of the intellectual landscape and research evolution of AI-driven banking risk management from 2020 to 2024. Full article

This review paper synthesizes the application and evolution of environmentally extended input–output (EEIO) analysis in agricultural research, drawing on 647 publications (Scopus and Web of Science, 1978–2025) following the PRISMA method and using the Bibliometrix package in the R statistical computing environment. EEIO has become a leading method for assessing system-level environmental impacts by quantifying direct and indirect flows across complete supply chains. Bibliometric and thematic analyses reveal accelerated growth since 2015 and four principal domains of enquiry: emissions embodied in trade, water-resource management, energy and climate impacts, and the sustainability of agri-food supply chains. EEIO’s principal value lies in its capacity to support production- versus consumption-based accounting and to reveal intersectoral trade-offs that single-sector approaches overlook. However, standard EEIO frameworks remain constrained by fixed technical coefficients, coarse sectoral aggregation, and uncertainty in environmental extensions, which limit their capacity to resolve farm-scale processes, structural change, and feedbacks. To enhance analytical rigor and policy relevance, we advocate hybridization with life-cycle and farm-level data, development of higher-resolution multi-regional EEIO tables, incorporation of stochastic and scenario analyses, dynamic formulations to capture technological change, and adoption of open-data standards with transparent reporting. Advancing these priorities will improve comparability, reproducibility and the practical uptake of EEIO for evidence-based transitions in agricultural systems. Full article

This study presents a bibliometric analysis of 461 studies on refugee and (im)migrant education governance, covering the period from 2015 to 2025. All studies were articles indexed in the Web of Science category. The analysis reveals publication trends, conceptual and intellectual structures, and the evolution of themes. Data were analyzed using the Bibliometrix R package. Document coupling and thematic analyses indicate a modular research ecosystem structured around policy governance, inclusion and diversity, refugee education, and access to higher education, with governance-focused scholarship playing a prominent connective role. A systematic review, guided by the PRISMA technique, was conducted to enhance these structural insights, focusing on the 25 most cited and conceptually significant studies identified during the bibliometric phase. The systematic review examined research features, participant demographics, educational settings, and analytical frameworks, with particular attention to the theoretical and operational aspects of governance, bordering, and surveillance themes. The findings reveal a pronounced geographic concentration in affluent Western contexts, especially the United States, alongside a smaller but conceptually significant body of work situated in refugee-hosting regions of the Global South. Education systems are consistently described as mechanisms of migratory governance, in which policies, accountability frameworks, and routine institutional activities establish borders and surveillance. This study combines extensive bibliometric mapping with comprehensive systematic synthesis to present a coherent overview of the conceptualization of refugee and (im)migrant education over the past decade, highlighting ongoing theoretical fragmentation and the need for more cross-scalar, integrative strategies in education governance within migration contexts. Full article

Despite extensive research on financial literacy and financial decision-making, the scholarly literature remains conceptually fragmented, particularly regarding how behavioral biases mediate or moderate the relationship between knowledge and financial behavior. The existing literature often focuses on financial literacy or behavioral biases in isolation, limiting a systematic understanding of their interaction. This study addresses this gap by conducting a bibliometric analysis of research at the intersection of financial literacy, behavioral finance, and decision-making. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we analyzed 267 peer-reviewed publications indexed in Web of Science and Scopus over the period 2010–2025 using the Bibliometrix 5.2.1 R package and VOSviewer 1.6.20 for co-occurrence, thematic clustering, and trend analysis. The results identify three interconnected research clusters: (i) socio-demographic and educational determinants of financial literacy, (ii) cognitive and behavioral biases influencing financial decision processes, and (iii) applied investment decision contexts. Overconfidence and herding dominate the literature, whereas biases such as framing, mental accounting, and intertemporal inconsistency remain comparatively underexplored. The analysis further reveals a post-2022 surge in publications, increasing internationalization, and emerging integration of digital finance and artificial intelligence themes. By systematically mapping the intellectual structure of this research domain, this study clarifies theoretical fragmentation, identifies under-researched behavioral mechanisms, and provides an evidence-based framework to guide future interdisciplinary and policy-relevant research on how financial literacy translates into financial behavior. Full article

With the acceleration of digital transformation in education, this paper examines how blockchain is being framed as a governance solution for trust, transparency, and decentralization. Using a hybrid bibliometric and thematic analysis of 93 Web of Science and Scopus publications, the study maps publication trends, leading outlets, author networks, and conceptual clusters. We analyze co-authorship networks, keyword co-occurrence patterns, and conceptual structures using VOSviewer version 1.6.19 and the R-based Bibliometrix package. Then, we apply qualitative coding to offer a more profound interpretation of governance stories. Findings show that blockchain in educational governance is predominantly positioned through techno-managerial lenses—focusing on secure credentials, tamper-proof records, and efficiency—while critical perspectives on power, equity, and participation remain limited. Global North institutions and computer science–oriented venues dominate the field, with little engagement from Global South contexts or educational leadership scholarship. The paper concludes by proposing a research agenda that reimagines blockchain not as a neutral tool, but as a socio-technical assemblage that must be interrogated through equity-, ethics-, and community-centered frameworks. Full article

Modern road infrastructure asset management faces increasing pressure to improve the quality of decision-making processes, also due to limited public resources. The field of road diagnostics is no exception. The aim of the research is to analyze, through a literature review, the possibilities of applying the theoretical concept of information value. The selected point of interest is the tasks associated with the selection of specific sections intended for inspection, monitoring the level of information gain that this inspection can bring. Methodologically, the research is based on a systematic bibliometric analysis of the literature from the Web of Science and SCOPUS databases for the period January 2010 to June 2025. This is supplemented by a non-systematic content review, while the identified publications were processed by the Bibliometrix and VOSviewer tools and subsequently qualitatively interpreted. The result of the research is a synthesis of knowledge from the finally analyzed set of relevant scientific papers. The findings point to a growing interest in linking the process of planning and performing road infrastructure diagnostics with asset management decision-making processes. At the same time, they point to the development of data-oriented and digital approaches, as well as the limited application of the concept of information value in planning inspections before their implementation. The findings indicate that the assessment of expected information benefit represents a promising tool for reducing uncertainty, determining priorities, and allocating resources more efficiently, while its implementation in road infrastructure management requires further methodological research and practical verification. Full article

This study aims to systematically analyze scholarly research on virtual reality (VR), augmented reality (AR), and the metaverse in the tourism and hospitality sectors, offering insights into publication patterns, key contributors, thematic evolution, and potential research directions from 2016 to mid-2025. It maps how the literature evolved in response to technological maturation and changing tourism constraints. A systematic literature review and comprehensive bibliometric analysis were conducted using the Scopus database. The analysis encompassed bibliographic metrics, thematic clustering, and content analysis techniques to identify influential journals, authors, and evolving research themes. The results reveal a pronounced acceleration in research activity post-2020, reflecting heightened interest due to the COVID-19 pandemic’s push towards digital and immersive solutions. Core journals identified include Tourism Management, Current Issues in Tourism, and Journal of Travel Research. Influential contributors such as Timothy H. Jung, M. Claudia tom Dieck, and Dimitrios Buhalis significantly shaped the field. The thematic trajectory demonstrates a shift from initial exploration and application of VR and AR technologies toward comprehensive integration into metaverse ecosystems, with emerging themes such as digital twins, synthetic experiences, immersive storytelling, and growing emphasis on ethical and sustainability considerations. By synthesizing nearly a decade of research, this study provides valuable insights into immersive technologies’ evolution in tourism and hospitality, identifying critical areas for future investigation aligned with enterprise information management strategies. Full article

This systematic review evaluates recent scientific and technological advances in water quality monitoring and pollution alarms for ports, based on records retrieved from seven databases following the PRISMA protocol. A total of 414 documents were screened, resulting in 141 articles (TRL 3) and 56 patents (TRL 4–5). Bibliometric, patentometric, and thematic analyses were conducted using Bibliometrix and ORBIT^®. Results show sustained growth in both academic and technological outputs, with a patent Compound Annual Growth Rate (CAGR) of 32%, compared with 13% for scientific publications, indicating accelerated translation from research to innovation. The conversion rate from scientific research to patenting increased from 14% (2010–2015) to 47% (2020–2023). Analysis of patent legal status reveals that 52% of patent families remain valid (48% granted; 4% pending), while 33% are lapsed, 13% revoked, and 2% expired, reflecting the dynamic and emerging character of the field. Technological ownership is highly concentrated, with China accounting for nearly all active patents, whereas scientific production is more geographically distributed. Thematic analysis identifies four main scientific clusters: environmental monitoring, chemical pollutants, seashore hazards, and eutrophication. The main technological domains of the patents are analysis of biological materials, control, and environmental technologies. Emerging areas of focus at TRL 3 and TRL 4–5 include microplastics, climate-change impacts, aquaculture risks, real-time sensing, IoT-enabled platforms, machine-learning analytics, autonomous monitoring systems, and bioindicator-based early-warning tools. This review provides a quantitative roadmap to support sustainable port operations, coastal ecosystem protection, and progress toward multiple synergistic United Nations Sustainable Development Goals (SDGs). Full article

Additive Manufacturing (AM) and Wearable Technologies (WT) have rapidly evolved over the past decade. AM offers highly customisable fabrication, while WT enables minimally invasive health monitoring. The intersection of these fields presents emerging opportunities in biomedical and engineering domains. This study aims to map the scientific landscape of AM–WT research between 2015 and 2025 through a comprehensive bibliometric analysis. A total of 718 peer-reviewed publications were extracted from Web of Science (WoS), Scopus, and PubMed, following PRISMA-ScR guidelines. Using RStudio and the Bibliometrix package, analyses included co-authorship, citation trends, keyword co-occurrence, and thematic mapping. Custom author disambiguation scripts enhanced data quality and reliability. An annual publication growth of 24.89% was observed, with notable increases after 2020. Core themes included 3D printing, biosensors, microfluidics, and organ-on-a-chip devices. A shift from manufacturing-oriented research to biomedical integration is evident. Research output is dominated by the US, China, and South Korea, with moderate but not yet highly internationalised collaboration. The field of AM–WT research is undergoing a decisive transition from fabrication-focused studies to interdisciplinary, application-driven innovations. This shift is marked by increasing integration in healthcare and bioelectronics, yet hindered by regional imbalances and thematic gaps. Addressing these will be critical to advancing global impact. This study offers a cross-database bibliometric overview of AM–WT research. By combining three major data sources, it provides enhanced coverage and introduces novel analytical dimensions to guide future interdisciplinary efforts in personalised healthcare and wearable device innovation. Full article