ArticleJournal of neurological surgery. Part B, Skull base2026
ChatNSG: An Overview of Contemporary and Emerging Artificial Intelligence Models for the Neurosurgeon.
Article in Journal of neurological surgery. Part B, Skull base, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
7 authors.
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Abstract
Artificial intelligence (AI) is rapidly transforming health care, with significant implications for neurosurgery. This essay provides a focused overview of contemporary and emerging AI models relevant to neurosurgery, with particular emphasis on natural language processing (NLP) tools such as large language models (LLMs) and retrieval augmented generation systems. We present a framework for conceptualizing the AI-user relationship, emphasizing a collaborative model that promotes iterative refinement of queries and responses. The paper offers guidance on AI model selection for various neurosurgical tasks, highlighting the strengths of different AI types such as NLP models and machine learning algorithms. We introduce prompt engineering as a critical skill for neurosurgeons, providing practical tips and examples to optimize AI interactions. The review also discusses current limitations of AI in neurosurgery, including dataset biases and ethical considerations. By addressing these key areas, this article serves as a practical guide for neurosurgeons at all career stages to effectively integrate AI tools into their work, ultimately enhancing patient care, research capabilities, and educational practices in the field of neurosurgery.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.