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J Neurol Surg B Skull Base
DOI: 10.1055/a-2678-8460
Original Article

ChatNSG: An Overview of Contemporary and Emerging Artificial Intelligence Models for the Neurosurgeon

Kishore Balasubramanian 
1   Department of Neurosurgery, University of Oklahoma College of Medicine, Oklahoma City, Oklahoma, United States
2   College of Medicine, Texas A&M University, College Station, Texas, United States
,
Christopher Janssen
2   College of Medicine, Texas A&M University, College Station, Texas, United States
,
Ali S. Haider
3   School of Management, Rice University, Houston, Texas, United States
,
Visish M. Srinivasan
4   Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States
,
Daniel A. Donoho
5   Division of Neurosurgery, Children's National Medical Center, Washington, Dist. of Columbia, United States
,
Nicholas Sader
1   Department of Neurosurgery, University of Oklahoma College of Medicine, Oklahoma City, Oklahoma, United States
,
Christopher S. Graffeo 
1   Department of Neurosurgery, University of Oklahoma College of Medicine, Oklahoma City, Oklahoma, United States
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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.

Keywords

artificial intelligence - large language models - prompt engineering - neurosurgery


Publikationsverlauf

Eingereicht: 28. März 2025

Angenommen: 06. August 2025

Artikel online veröffentlicht:
19. August 2025

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