Latest AI and machine learning research in neurosurgery for healthcare professionals.
Artificial intelligence (AI) is increasingly integrated into neuroradiology practice, with a growing number of FDA-cleared algorithms now supporting tasks ranging from acute triage to volumetric analysis. This review provides a structured overview of commercially available, FDA-regulated AI tools in neuroradiology, organized by clinical application. These include detection and prioritization of in...
Abdominal aortic aneurysm (AAA) is a chronic degenerative disease characterized by localized aortic dilation and persistent inflammation. While neutrophil extracellular traps (NETs) are increasingly recognized as key drivers of vascular inflammation and aneurysm progression, the transcriptomic landscape of NETs-related genes (NRGs) in AAA remains inadequately characterized. This study aimed to ide...
Large Language Models (LLMs) show strong potential for extracting structured information from unstructured clinical narratives. However, their adoptio...
BACKGROUND AND OBJECTIVES: General purpose vision-language models (VLMs) demonstrate impressive capabilities, but their opaque training on uncurated i...
Tumor stiffness and adhesion are decisive factors in neurosurgical strategy, yet they remain absent from standard planning and navigation. Advances in...
BACKGROUND AND OBJECTIVE: Underlying biomechanical instability of the vessel wall is believed to drive the substantial morphological variability obser...
Early and accurate detection of intracranial aneurysms (IAs) is critical for preventing rupture; however, manual interpretation of time-of-flight magn...
Intraoperative neurophysiological monitoring (IONM) has evolved from a novel technique into an evidence-based standard treatment method for high-risk ...
Pediatric neurosurgery increasingly utilizes precision medicine, but practitioners encounter challenges in translating complex data into individualize...
Artificial intelligence shows promise for improving care for peripheral artery disease through earlier detection, improved risk stratification, more t...
BACKGROUND: Percutaneous endoscopic interlaminar discectomy (PEID) is a common surgical technique for lumbar disc herniation (LDH), but the risk facto...
Thoracic aortic aneurysms arise from a combination of biological and mechanical factors. Current clinical guidelines use size and rate of expansion to...
The main goal of this paper is to determine the optimal DC bias value for DC-biased optical orthogonal frequency division multiplexing (DCO-OFDM)- bas...
BACKGROUND: Long-term follow-up is essential for patients with abdominal aortic aneurysms (AAAs). Our health system implemented an AAA surveillance pr...
Predicting isocitrate dehydrogenase (IDH) mutations in gliomas using magnetic resonance imaging (MRI) is clinically important for treatment planning. ...
BACKGROUND: There is a lack of research about artificial intelligence's potential to explore neurosurgical literature. We aimed to investigate ChatGPT...
Endovascular aneurysm repair for ruptured abdominal aortic aneurysms (RAAAs) is technically demanding due to time pressure and distorted vascular anat...
Generative artificial intelligence (AI) has emerged as a transformative tool for creating high-quality visual materials in medical research and educat...
Large language models (LLMs) are rapidly transforming healthcare, yet their implications for pediatric neurosurgery remain underexplored. This narrati...
BACKGROUND AND PURPOSE: To develop a comprehensive multi-modal framework for assessing the rupture risk of intracranial aneurysms and predicting inter...