METHODS: A literature review examined how far such frameworks exist, with a view to identifying conducive factors - and crucial gaps. This extensive review of key factors across 22 countries and 5 regions revealed a wide variety of attitudes, approaches, provisions and conditions, and permitted the construction of a comprehensive overview of the current status of PM. Based on seven key pillars identified from the literature review and expert panels, the data was quantified, and on the basis of further analysis, an index was developed to allow comparison country by country and region by region.
RESULTS: The results show that United States of America is leading according to overall outcome whereas Kenya scored the least in the overall outcome.
CONCLUSIONS: Still, common approaches exist that could help accelerate take-up of opportunities even in the less prosperous parts of the world.
METHODS: This bibliometric work investigated the academic publication trends in medical image segmentation technology. These data were collected from the Web of Science (WoS) Core Collection and the Scopus. In the quantitative analysis stage, important visual maps were produced to show publication trends from five different perspectives including annual publications, countries, top authors, publication sources, and keywords. In the qualitative analysis stage, the frequently used methods and research trends in the medical image segmentation field were analyzed from 49 publications with the top annual citation rates.
RESULTS: The analysis results showed that the number of publications had increased rapidly by year. The top related countries include the Chinese mainland, the United States, and India. Most of these publications were conference papers, besides there are also some top journals. The research hotspot in this field was deep learning-based medical image segmentation algorithms based on keyword analysis. These publications were divided into three categories: reviews, segmentation algorithm publications, and other relevant publications. Among these three categories, segmentation algorithm publications occupied the vast majority, and deep learning neural network-based algorithm was the research hotspots and frontiers.
CONCLUSIONS: Through this bibliometric research work, the research hotspot in the medical image segmentation field is uncovered and can point to future research in the field. It can be expected that more researchers will focus their work on deep learning neural network-based medical image segmentation.
METHOD: This study presents the publication trends, research landscape, and scientific developments related to safety management systems (SMS) based on published documents from the Elsevier Scopus database. Published documents on SMS and indexed in Scopus are identified, screened, and analyzed to examine the publication trends, research developments, and scientific landscape. For this purpose, Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), bibliometric analysis (B.A.), and systematic literature review (SLR) procedures are used. The results reveal that 799 related documents were published between 2001 and 2021.
RESULTS: The most productive stakeholders, that is, top researchers, affiliations, and countries, include Liesbeth Jacxsens, Universiteit Gent (Belgium), and the United States. This study shows that the availability of research grants, incentives, or awards is critical to the productivity of top researchers, institutions, and nations actively researching SMS topics. The bibliometric analysis reveals that the topic is characterized by high productivity, co-authorships, keyword occurrence, and citations.
CONCLUSION: The analysis shows that SMS research is a broad, multidimensional, and impactful area that has become essential for identifying, reducing, monitoring, and eliminating risks in many industries. It is concluded that the topic of the SMS remains relevant because of its impact on human health, occupational safety, and environmental well-being.
PRACTICAL APPLICATIONS: This study provides in-depth insight into expanding the scope of SMS research. Moreover, research and policymakers can facilitate decision-making and collaboration based on this study's outtakes.