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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. Web of Sciences database was searched, and a list of the top 50 most cited articles, assessing the application of ML in stroke, was prepared by 2 authors, independently. Subsequently, a detailed analysis was performed to characterize the most impactful studies. The total number of citations to the top 50 articles were 2959 (range 35–243 citations) with a median of 47 citations. Highest number of articles were published in the journal Stroke and the United States was the major contributing country. The majority of the studies focused on the utilization of ML to improve stroke risk prediction, diagnosis, and outcome prediction. Statistical analysis revealed an insignificant association between the total and mean number of citations and the impact factor of the journal (P = 0.516 and 0.987, respectively). 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. [ABSTRACT FROM AUTHOR]

To conduct a quantitative analysis of published studies on hematoma enlargement after intracerebral hemorrhage. Studies on hematoma enlargement after cerebral hemorrhage were retrieved from the Web of Science database on June 30, 2023. Microsoft Excel, VOSviewer, and CiteSpace software were used for bibliometric analysis and visualization, focusing on the quantitative characteristics of the literature. A total of 444 articles were published in 161 journals, with 2161 authors from 41 countries and 717 institutions. The most published authors, countries, and institutions were Goldstein, the USA, and Massachusetts General Hospital. Stroke published the most studies, but the average citation number per year of Lancet Neurology far exceeded that of other journals. The research field of hematoma enlargement is mainly divided into 3 focuses, including mechanisms, identification (computed tomography signs, predictive models), and treatment (hemostasis, antihypertensive therapy). Most bursts in publication number have been since 2010, where the highest burst was from research on spot signs, and the latest burst focused on tranexamic acid. Treatment using tranexamic acid based on different computed tomography signs is a focus of current research, but the effectiveness still requires further exploration. 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. [ABSTRACT FROM AUTHOR]