Presurgical evaluation with functional magnetic resonance imaging (fMRI) can reduce
postsurgical morbidity. Here, we discuss presurgical fMRI mapping at ultra-high magnetic …

Until recently, innovations in surgery were largely represented by extensions or
augmentations of the surgeon's perception. This includes advancements such as the …

Background Large Language Models (LLMs) have garnered increasing attention in
neurosurgery and possess significant potential to improve the field. However, the breadth …

The early and accurate diagnosis of brain tumors is critical for effective treatment planning,
with Magnetic Resonance Imaging (MRI) serving as a key tool in the non-invasive …

Background and Objective Preoperative neurosurgical planning is a keen step to avoiding
surgical complications, reducing morbidity, and improving patient safety. The incursion of …

Background: This study investigates the application of Machine Learning techniques to
predict clinical outcomes in microsurgical clipping treatments of cerebral aneurysms, aiming …

AI technologies are also making strides in surgical simulation and training, offering
neurosurgeons enhanced opportunities to practice and refine their skills in a riskfree …

The emergence of artificial intelligence (AI) in the medical field holds promise in improving
medical management, particularly in personalized strategies for the diagnosis and treatment …

Abstract Introduction Artificial Intelligence (AI) applications in healthcare are growing
exponentially. The field of neurosurgery is particularly suited to implement AI solutions given …

Surgical planning for TSC, particularly for epilepsy surgery, is complex due to the multifocal
nature of the disease and the presence of multiple lesions in the brain. The goal is to …