METHODS: We employed a methodical bibliometric approach, making use of Scopus and Web of Science (WoS) databases for gathering literatures. We planned our search strategy, concentrating on terms linked to "breast imaging," "image quality," and "diagnostic accuracy" to ensure a systematic examination of the subject. The enhanced search functions in these databases enabled us to narrow down and improve our findings, choosing only the articles, conference papers, and book sections that are most relevant. After conducting a thorough screening process to remove duplicates and evaluate significance, we utilized ScientoPy and VOSviewer software for an in-depth bibliometric analysis. This helped to explore trends in publications, patterns of citations, and thematic groups, giving us a better understanding of how the field has changed and where it currently stands. Our approach prioritized assessing methodological quality and bias in the studies we included, guaranteeing the reliability of our findings.
RESULTS: We reviewed 2984 relevant publications, revealing a consistent annual growth rate of 2.8% in breast imaging research, with the United States and Europe leading in contributions. The study found that advancements in radiological technologies and international collaboration are driving forces behind the field's expansion. Key subject areas such as 'Radiology, Nuclear Medicine, and Medical Imaging' dominated, underscoring their impact on diagnostic quality. Notable authors and institutions have been identified for their influential research, characterized by high citation metrics and significant scholarly impact.
CONCLUSION: The study shows a continuous increase in research on breast imaging, considered by new technologies and teamwork defining the present time. The assessment highlights a key move towards utilizing digital imaging methods and computational analysis, affecting the improvement of future diagnostic procedures and patients' results. The study highlights the importance of continued international collaborations to tackle the new barriers in breast imaging and make the most of technological progress.
IMPLICATIONS FOR PRACTICE: This study shows a focus on using interdisciplinary methods and cutting-edge technology in breast imaging to help healthcare professionals improve their performance and accuracy in diagnosis. Recognizing vital research and emerging trends should guide clinical guidelines, radiology training, and patient care plans to encourage the use of effective techniques and stimulate innovation in diagnostic approaches.
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.
METHODS: Scoping review methodology guided the synthesis of 272 publications on factors influencing physical activity. Bibliometric analysis examined publication trends, productivity, influential studies, content themes, and collaboration networks.
RESULTS: Since 2010, the United States has led a significant increase in research output. Highly cited articles identified physiological limitations and psychosocial determinants as key barriers and facilitators. Extensive focus was seen in clinical medicine and exercise science journals. Analysis revealed predominant attention to psychosocial factors, physiological responses, and applications in respiratory disease. Gaps remain regarding policy and environmental factors.
CONCLUSION: This review showed major advances in elucidating determinants while revealing the remaining needs to curb the pandemic of inactivity globally. Expanding international collaboration, contemporary theoretical models, and tailored mixed-methods approaches could promote progress through greater global participation. Addressing knowledge gaps across populations and disciplines should be a priority.