AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Neurosurgical Procedures

Showing 101 to 110 of 201 articles

Clear Filters

Endonasal endoscopic transsphenoidal approach robot prototype: A cadaveric trial.

Asian journal of surgery
BACKGROUND: The Endonasal Endoscopic Transsphenoidal Surgery (EETS) is a minimally invasive procedure to approach and remove pituitary tumors and other sellar lesions. The process causes less pain, faster recovery, and provides further minimal invasi...

Temporal Lobe Epilepsy Surgical Outcomes Can Be Inferred Based on Structural Connectome Hubs: A Machine Learning Study.

Annals of neurology
OBJECTIVE: Medial temporal lobe epilepsy (TLE) is the most common form of medication-resistant focal epilepsy in adults. Despite removal of medial temporal structures, more than one-third of patients continue to have disabling seizures postoperativel...

Technologic Evolution of Navigation and Robotics in Spine Surgery: A Historical Perspective.

World neurosurgery
Spine surgery is continuously evolving. The synergy between medical imaging and advances in computation has allowed for stereotactic neuronavigation and its integration with robotic technology to assist in spine surgery. The discovery of x-rays in 18...

Machine learning in neurosurgery: a global survey.

Acta neurochirurgica
BACKGROUND: Recent technological advances have led to the development and implementation of machine learning (ML) in various disciplines, including neurosurgery. Our goal was to conduct a comprehensive survey of neurosurgeons to assess the acceptance...

Pituitary Tumors in the Computational Era, Exploring Novel Approaches to Diagnosis, and Outcome Prediction with Machine Learning.

World neurosurgery
BACKGROUND: Machine learning has emerged as a viable asset in the setting of pituitary surgery. In the past decade, the number of machine learning models developed to aid in the diagnosis of pituitary lesions and predict intraoperative and postoperat...

The Future of Skull Base Surgery: A View Through Tinted Glasses.

World neurosurgery
In the present report, we have broadly outlined the potential advances in the field of skull base surgery, which might occur within the next 20 years based on the many areas of current research in biology and technology. Many of these advances will a...

Fully automated brain resection cavity delineation for radiation target volume definition in glioblastoma patients using deep learning.

Radiation oncology (London, England)
BACKGROUND: Automated brain tumor segmentation methods are computational algorithms that yield tumor delineation from, in this case, multimodal magnetic resonance imaging (MRI). We present an automated segmentation method and its results for resectio...

Development of machine learning-based preoperative predictive analytics for unruptured intracranial aneurysm surgery: a pilot study.

Acta neurochirurgica
BACKGROUND: The decision to treat unruptured intracranial aneurysms (UIAs) or not is complex and requires balancing of risk factors and scores. Machine learning (ML) algorithms have previously been effective at generating highly accurate and comprehe...

Development of machine learning and natural language processing algorithms for preoperative prediction and automated identification of intraoperative vascular injury in anterior lumbar spine surgery.

The spine journal : official journal of the North American Spine Society
BACKGROUND: Intraoperative vascular injury (VI) may be an unavoidable complication of anterior lumbar spine surgery; however, vascular injury has implications for quality and safety reporting as this intraoperative complication may result in serious ...