Articles: bibliometric-analysis.
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Though currently considered a 'black box,' machine learning (ML) has a promising future to ameliorate the health-care burden of stroke which is the second leading cause of mortality worldwide. Through this study, we sought to review the most influential articles on the applications of ML in stroke. ⋯ Recent years have witnessed a surge in the application of ML in stroke, with an enhancement in interest and funding over the years. ML has revolutionized the management of stroke and continues to aid in the neurosurgical decision-making and care in stroke patients.
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Since tethered cord syndrome (TCS) may lead to neurologic and motor dysfunction, surgeries often are applied to relieve the symptoms. The aim of the research was to explore the current global research trends of TCS surgery. ⋯ This study will help researchers to identify the mainstream research directions and the latest hotspots in the field of TCS surgery and provide a reference for further research.
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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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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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Review
A Bibliometric Analysis of Top-Cited Journal Articles Related to Neuromodulation for Chronic Pain.
Since its foundation in the 1960s, neuromodulation has become an increasingly used treatment option for chronic pain. This bibliometric analysis examines the most cited research in this field with the aim of uncovering existing trends and future directions. ⋯ Analysis of the most cited articles on neuromodulation reveals a focal shift from historical reports to innovative RCTs that have increasingly guided pain practice in the recent years. As novel techniques and technologies continue to develop, high-quality evidence coupled with broadening indications will likely direct further expansion of this field.