Latest AI and machine learning research in neurosurgery for healthcare professionals.
Structured light (SL) 3D reconstruction captures the precise surface shape of objects, providing high-accuracy 3D data essential for industrial inspection and robotic vision systems. However, current research on optimizing projection patterns in SL 3D reconstruction faces two main limitations: each scene requires separate training of calibration parameters, and optimization is restricted to spec...
Quantization for deep neural networks (DNNs) is the process of mapping the parameter values of DNNs from original data types to other data types of lower precision to reduce model sizes and make inference faster. Quantization often maps different original values to a single quantized value because the range of the original values is larger than the range of the quantized values. This leads to th...
Intracranial aneurysm (IA) is a common cerebrovascular disease that is usually asymptomatic but may cause severe subarachnoid hemorrhage (SAH) if ru...
Large language models (LLMs) have demonstrated remarkable performance across various machine learning tasks, quickly becoming one of the most preval...
Thoracic aortic aneurysms (TAAs) arise from a combination of biological and mechanical factors. Current clinical guidelines use size and rate of expan...
Aortic aneurysms, including abdominal (AAA) and thoracic (TAA), pose significant challenges due to their rupture risk and complex pathophysiology. Whi...
Early identification of individuals at high risk for aneurysms, particularly ruptured aneurysms, is critical for timely intervention. However, existin...
A comprehensive analysis of artificial intelligence’s (AI) integration into neurosurgery is vital to identify research priorities, address gaps, and i...
Cerebral aneurysm is a silent yet prevalent condition that affects a substantial portion of the global population. Aneurysms can develop due to variou...
Surgical success hinges on two core factors: technical execution and cognitive planning. While the former can be trained and potentially augmented thr...
Rare or unexpected postoperative neurosurgical complications pose a challenge due to clinical variability and gaps in available data. We introduce the...
Precise aneurysm volume measurement offers a transformative edge for risk assessment and treatment planning in clinical settings. Currently, clinical ...
Proteomic techniques now measure thousands of proteins circulating in blood at population scale, driving a surge in biomarker studies and biological c...
Traditional medical board examinations present clinical information in static vignettes with multiple-choices, fundamentally different from how physic...
Real-time brain monitoring for neurosurgery and neuroscience research of natural behaviors demands portable imaging with high spatiotemporal resolutio...
Automated interpretation of resting-state fMRI (rs-fMRI) for epilepsy diagnosis remains a challenge. We developed a regularized transformer that model...
Clinical guidelines recommend using an absolute ascending aortic diameter (AAD) cutoff of 4.5 cm for monitoring and 5.5 cm for surgery in people at ri...
Pediatric brain tumors are the leading cause of cancer death in children, with surgical resection critical for survival and neurodevelopment. Intraope...
To evaluate how reader experience influences the diagnostic benefit from LLM assistance in brain MRI differential diagnosis. Neuroradiologists (n = 4)...
MRI-derived organ and tissue volumes are powerful endophenotypes for studying complex disease, but their availability is limited by cost and throughpu...