Artificial intelligence and robotics in global neurosurgery: A scoping review

Authors

Document Type

Journal Article

Publication Date

6-1-2026

Journal

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia

Volume

148

DOI

10.1016/j.jocn.2026.111978

Keywords

Artificial intelligence; Global health; Global neurosurgery; Robotics

Abstract

OBJECTIVE: Artificial intelligence (AI) and robotics are transforming neurosurgical care; however, the application of these technologies in low- and middle-income countries (LMICs), where the burden of neurosurgical diseases is highest, is not well-characterized. In this scoping review, we sought to map the current landscape of AI and robotics in global neurosurgery to identify themes and gaps that can catalyze the expansion of safe neurosurgical care worldwide. METHODS: A systematic search was conducted across MEDLINE/PubMed, Embase, Web of Science, and IEEE Xplore. This review followed the Population, Concept, and Context (PCC) framework, including studies that utilized AI or robotics for neurosurgical diagnosis, decision-making, or treatment in global developing or low-resource settings. RESULTS: A total of 22 studies were identified, with a rapid acceleration in research observed since 2023. Geographically, the majority of applications were in Africa (n = 13), followed by Asia (n = 6) and South America (n = 4). Trauma was the predominant field (n = 11), where machine learning was frequently used for triage and prognostication. Other common applications included AI for brain tumor classification and segmentation, automated stroke detection, and image-guided surgical robotics, with models trained on local data outperforming those imported from other settings. Nineteen of the 22 studies included coauthors from the region of application, and 16 included coauthors from a HIC. CONCLUSION: AI and robotics are demonstrating increasing utility in supporting global neurosurgery by augmenting workforce capacity and improving efficiency of care. However, success depends heavily on data representation. Future work should focus on supporting local research capacity and leadership and expanding applications to postoperative care.

Department

Neurological Surgery

Share

COinS