Neurosurgery and Artificial Intelligence: A Metric Analysis of Scopus-Indexed Original Articles (2014-2023)
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Introduction
A comprehensive analysis of artificial intelligence’s (AI) integration into neurosurgery is vital to identify research priorities, address gaps, and inform strategies for equitable innovation.
Objective
To conduct a bibliometric analysis of Scopus-indexed (2014-2023) original articles at the intersection of AI and neurosurgery.
Method
A descriptive metric study was conducted on 91 original articles, employing productivity, impact, and collaboration indicators. SciVal facilitated data extraction, while VOSviewer 1.6.11 enabled the mapping of co-authorship networks and keyword co-occurrence. IBM SPSS Statistics 27 was used to determine correlations between variables of interest (Kendall’s rank correlation coefficient, statistically significant for p < 0.05).
Results
The 91 articles accumulated 2,197 citations (24.1/article), reflecting rising productivity. Most highly cited works (2019–2023) were published in Q1 journals. Dominant neurosurgical areas included neuro-oncology (25.4%) and education (20.9%), with AI applications focused on diagnostic accuracy (20.9%) and predictive tools (17.6%). Citations correlated with author numbers (p = 0.007). World Neurosurgery led in publications (Ndoc = 11), while JAMA Network Open had the highest citations/article (88.7). Author, institutional, and country productivity correlated strongly with citations (p < 0.001). Collaboration was universal (international: 29.7%, national: 53.8%, institutional: 16.5%).
Conclusions
The analyzed scientific output exhibited a marked quantitative growth trend and high citation rates, with a predominant focus on leveraging AI to enhance diagnostic accuracy, particularly in neuro-oncology. Publications were concentrated in specialized, high-impact journals and predominantly originated from authors and institutions in high-income, technologically advanced Northern Hemisphere countries, where scientific collaboration played a foundational role in driving research advancements.