Latest AI and machine learning research in neurosurgery for healthcare professionals.
In this report, we present a 55-year-old female with cervical stenosis that underwent C5-C7 anterior...
Intracerebral hemorrhage (ICH) is a stroke subtype with high mortality and disability, and there are...
BACKGROUND: With advances in science and technology, the application of artificial intelligence in m...
Intracranial hemorrhage (ICH) from traumatic brain injury (TBI) requires prompt radiological investi...
Multi-parametric MR image synthesis is an effective approach for several clinical applications where...
Surgical data quantification and comprehension expose subtle patterns in tasks and performance. Enab...
During surgery for foci-related epilepsy, neurosurgeons face significant difficulties in identifying...
"Image-based" computational fluid dynamics (CFD) simulations provide insights into each patient's he...
OBJECTIVE: Interspinous motion (ISM) is a representative method for evaluating the functional fusion...
Machine learning (ML) models are being actively used in modern medicine, including neurosurgery. Thi...
Brain tissue deformation during surgery significantly reduces the accuracy of image-guided neurosurg...
Electrocorticography (ECoG) is a minimally invasive approach frequently used clinically to map epile...
OBJECTIVE: The clinical ability of radiomics to predict intracranial aneurysm rupture risk remains u...
CTG (Cardiotocography) is an effective tool for fetal status assessment. Clinically, doctors mainly ...
 Surgery is the treatment of choice for growth hormone (GH)-secreting pituitary adenoma. The remiss...
The use of artificial intelligence in neurosurgical education has been growing in recent times. Chat...
BACKGROUND: Image-guided neurosurgery requires high localization and registration accuracy to enable...
STUDY DESIGN: A retrospective cohort study from a multisite academic medical center.
BACKGROUND: Minimally invasive vascular intervention (MIVI) is a powerful technique for the treatmen...