Artificial intelligence in neurosurgery: evidence, clinical applications and future perspectives
DOI:
https://doi.org/10.59156/revista.v40i01.792Keywords:
Artificial intelligence, Machine learning, Narrative review, NeurosurgeryAbstract
Background: artificial intelligence (AI) has emerged as one of the most disruptive tools in contemporary medicine, with a growing impact on neurosurgical practice. Its ability to process large volumes of data, identify complex patterns, and assist in surgical decision-making opens new possibilities in diagnosis, surgical planning, and medical education. However, its integration poses significant challenges. In this context, a narrative review with a systematic methodology is necessary to synthesize current evidence, explore the most relevant clinical applications, and analyze its prospects.
Objectives: to analyze the main evidence, applications, and perspectives of AI in neurosurgery.
Methods: a search was conducted in PubMed, Scopus, and Web of Science, adapting PRISMA criteria for narrative reviews. Studies in English and Spanish published between 2020 and October 2025 were included.
Results: of 412 selected records, 118 articles were analyzed after screening for relevance and methodological quality. AI shows significant impact on diagnosis, pre-surgical planning, and application in neurosurgical subspecialties. Large language models offer utility in education and physician-patient communication. Critical limitations include a lack of widespread external validation, algorithmic biases, nascent regulatory frameworks, and particular challenges in Latin America.
Conclusion: AI is a transformative tool in neurosurgery, but its responsible implementation requires rigorous validation, robust ethical and legal frameworks (especially adapted to the regional context), and constant human oversight. Professional training and the generation of local evidence are imperative for equitable and safe integration.
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