Latest AI and machine learning research in neurosurgery for healthcare professionals.
By replacing standard non-linearities with polynomial activations, Polynomial Neural Networks (PNN...
A generative model for the mesh geometry of intracranial aneurysms (IA) is crucial for training ne...
Vestibular schwannoma (VS) is the most prevalent intracranial schwannoma. Surgery is one of the opti...
: Lumbar spine surgery has undergone significant technological transformation in recent years, drive...
Endovascular Aneurysm Repair (EVAR) is a minimally invasive procedure crucial for treating abdominal...
BackgroundComputed tomography (CT) is widely used in clinical diagnosis of lung diseases. The automa...
Parkinson's disease (PD) is a progressive neurodegenerative disorder marked by motor and non-motor d...
Cerebral aneurysms are pathological dilations of intracranial arteries that can rupture with devas...
Purpose To evaluate a sham-artificial intelligence (AI) model acting as a placebo control for a stan...
BACKGROUND: The advancement of artificial intelligence (AI) has led to its application in various fi...
Quantization is a powerful tool to improve large language model (LLM) inference efficiency by util...
Adversarial patches are widely used to evaluate the robustness of object detection systems in real...
This study investigates the influence of aneurysm evolution on hemodynamic characteristics within ...
Differentially Private Stochastic Gradient Descent (DP-SGD) is a widely adopted technique for priv...
Despite the plethora of AI-based algorithms developed for anomaly detection in radiology, subseque...
Due to the limited accuracy of 4D Magnetic Resonance Imaging (MRI) in identifying hemodynamics in ...
Vision-Language Models (VLMs) leverage aligned visual encoders to transform images into visual tok...
Abdominal aortic aneurysms (AAAs) are localized dilatations of the abdominal aorta that can lead t...
Introduction: Timely care in a specialised neuro-intensive therapy unit (ITU) reduces mortality an...
Personalized federated learning is extensively utilized in scenarios characterized by data heterog...
Objective: ascending aortic aneurysm growth prediction is still challenging in clinics. In this st...