Artificial Intelligence and Machine Learning in Neurosurgery: Applications, Validation, and Translational Challenges

Artificial intelligence and machine learning are increasingly being applied across the neurosurgical workflow — from automated image segmentation and radiomics-based tumor characterization to intraoperative decision support, outcome prediction, and robotic assistance. This chapter critically reviews the current evidence base for AI applications in neurosurgery, assessing methodological quality, validation standards, and the gap between algorithmic performance and clinical implementation. It addresses the ethical, regulatory, and educational challenges associated with the responsible integration of AI tools into neurosurgical practice.