Neurosurgery and artificial intelligence: a bibliometric analysis of Scopus-indexed original articles (2014–2023)

Abstract Background 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 bibliometric 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 2197 citations (24.1/article), reflecting rising productivity. Most highly cited works (2019–2023) were published in Q1 journals. Dominant neurosurgical areas included education (20.9%), spine (16.5%), and neuro-oncology (15.4%), 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.

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Publication Details

Journal
The Egyptian Journal of Neurosurgery : the official publication of the Egyptian Society of Neurological Surgeons/Egyptian journal of neurosurgery
Published
2025-09-08
DOI
https://doi.org/10.1186/s41984-025-00466-x
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
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article

Neurosurgery and artificial intelligence: a bibliometric analysis of Scopus-indexed original articles (2014–2023)

Hector Julio Piñera-Castro, Christian Borges-García
The Egyptian Journal of Neurosurgery : the official publication of the Egyptian Society of Neurological Surgeons/Egyptian journal of neurosurgery
Artificial Intelligence in Healthcare and Education
article

Neurosurgery and artificial intelligence: a bibliometric analysis of Scopus-indexed original articles (2014–2023)

Hector Julio Piñera-Castro, Christian Borges-García
article en

Abstract

Abstract Background 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 bibliometric 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 2197 citations (24.1/article), reflecting rising productivity. Most highly cited works (2019–2023) were published in Q1 journals. Dominant neurosurgical areas included education (20.9%), spine (16.5%), and neuro-oncology (15.4%), 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.

The Egyptian Journal of Neurosurgery : the official publication of the Egyptian Society of Neurological Surgeons/Egyptian journal of neurosurgeryVol. 40(1)
Universidad de Ciencias Medicas (CR), Hermanos Ameijeiras Hospital (CU)
Openalex Percentile: Top 82%
Artificial Intelligence in Healthcare and Education
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