Articles: bibliometric-analysis.
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Background: Triggering receptor expressed in myeloid cells 2 (TREM2), a transmembrane receptor, has garnered extensive research attention due to its pivotal role in the diagnosis and treatment of various diseases. Despite the abundance of studies on its function, there is a gap in comprehensive analysis and summarization of the current state of this research field. Methods: Articles and reviews related to TREM2 were retrieved from the Web of Science Core Collection (WOSCC) on October 1, 2023. ⋯ Emerging directions such as metabolism and tumor microenvironment have recently gained attention in numerous studies. Conclusion: The current study utilizes bibliometric analysis software and visual graphics to intuitively highlight TREM2-related hotspots, trends, and prospects in human disease. Such insights are valuable for scholars seeking a deeper understanding of TREM2-related research progress, enabling a focused approach to its application in human disease.
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Background: Ischemic stroke is a common cerebrovascular accident with a high risk of neurological deficits. Stem cell therapy has progressively attracted the interest of scientists and clinicians due to the benefits of promoting neural regeneration and regulating the microenvironment surrounding the lesion after ischemic stroke. Our study aimed to evaluate the development trends and research hotspots in the field of stem cells and ischemic stroke. ⋯ The topics related to miRNA, extracellular vesicles, exosomes, mesenchymal stem cells, neuroinflammation, and autophagy are current research hotspots. Conclusion: Our bibliometric study provides a novel perspective on the research trends in the field of stem cells and ischemic stroke. The outcome of this study may benefit scientists to identify research hotspots and development directions, thereby advancing the application of stem cell-based therapy for ischemic stroke.
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To conduct a quantitative analysis of published studies on hematoma enlargement after intracerebral hemorrhage. ⋯ This bibliometric analysis analyzed the research framework and hotspots on hematoma enlargement after cerebral hemorrhage, which can help researchers better understand this field and provide potential suggestions for collaborations and research.
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The field of neurosurgery has consistently represented an area of innovation and integration of technology since its inception. As such, machine learning (ML) has found its way into applications within neurosurgery relatively rapidly. Through this bibliometric review and cluster analysis, we seek to identify trends and emerging applications of ML within neurosurgery. ⋯ This review highlights the most impactful articles pertaining to ML in the field of neurosurgery. ML has been applied into several sub-specialties within neurosurgery to optimize patient care, with special attention to outcome predictors, patient selection, and surgical decision making.
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Objectives: To identify the cooperation of authors, countries, institutions and explore the hot spots regarding research of renal cell carcinoma with venous tumor thrombus. Methods: Relevant articles were obtained from the Web of Science Core database (WoSC) from 1999 to 2024. CiteSpace was used to perform the analysis and visualization of scientific productivity and emerging trends. ⋯ Thrombectomy complications, thrombectomy survival outcome, and preoperative neoadjuvant immunotherapy represented the frontiers of research in this field, undergoing an explosive phase. Conclusion: This is the first bibliometric study that comprehensively visualize the research trends and status of RCC with VTT. We hope that this work will provide new ideas for advancing the scientific research and clinical application.