AI Medical Compendium Journal:
World neurosurgery

Showing 71 to 80 of 168 articles

Safety and Accuracy of Robot-Assisted Cervical Screw Placement: A Systematic Review and Meta-Analysis.

World neurosurgery
OBJECTIVE: The purpose of this study was to compare the accuracy and safety of robot-assisted (RA) cervical screw placement with conventional freehand (FH) technique.

Da Vinci Meets Globus Excelsius GPS: A Totally Robotic Minimally Invasive Anterior and Posterior Lumbar Fusion.

World neurosurgery
BACKGROUND: Minimally invasive approaches to the spine via anterior and posterior approaches have been increasing in popularity, culminating in the development of robot-assisted spinal fusions. The da Vinci surgical robot has been used for anterior l...

Deep-Learning-Based Model for the Prediction of Cancer-Specific Survival in Patients with Spinal Chordoma.

World neurosurgery
OBJECTIVE: Spinal chordomas are locally aggressive and frequently recurrent tumors with a poor prognosis. Previous studies focused on a Cox regression model to predict the survival of patients with spinal chordoma. We aimed to develop a more effectiv...

Traditional Machine Learning Methods versus Deep Learning for Meningioma Classification, Grading, Outcome Prediction, and Segmentation: A Systematic Review and Meta-Analysis.

World neurosurgery
BACKGROUND: Meningiomas are common intracranial tumors. Machine learning (ML) algorithms are emerging to improve accuracy in 4 primary domains: classification, grading, outcome prediction, and segmentation. Such algorithms include both traditional ap...

Lumbar Spinal Canal Segmentation in Cases with Lumbar Stenosis Using Deep-U-Net Ensembles.

World neurosurgery
BACKGROUND: Narrowing of the lumbar spinal canal, or lumbar stenosis (LS), may cause debilitating radicular pain or muscle weakness. It is the most frequent indication for spinal surgery in the elderly population. Modern diagnosis relies on magnetic ...

Deep Learning Approaches for Glioblastoma Prognosis in Resource-Limited Settings: A Study Using Basic Patient Demographic, Clinical, and Surgical Inputs.

World neurosurgery
BACKGROUND: Glioblastoma (GBM) is the most common brain tumor in the United States, with an annual incidence rate of 3.21 per 100,000. It is the most aggressive type of diffuse glioma and has a median survival of months after treatment. This study ai...

Identification of Origin for Spinal Metastases from MR Images: Comparison Between Radiomics and Deep Learning Methods.

World neurosurgery
OBJECTIVE: To determine whether spinal metastatic lesions originated from lung cancer or from other cancers based on spinal contrast-enhanced T1 (CET1) magnetic resonance (MR) images analyzed using radiomics (RAD) and deep learning (DL) methods.

Use of the Globus ExcelsiusGPS System for Robotic Stereoelectroencephalography: An Initial Experience.

World neurosurgery
BACKGROUND: Stereoelectroencephalography (SEEG) is a critical tool used in the identification of epileptogenic zones. Although stereotactic frame-based SEEG procedures have been performed traditionally, newer robotic-assisted SEEG procedures have bec...

External Validation of an Artificial Intelligence Device for Intracranial Hemorrhage Detection.

World neurosurgery
BACKGROUND: Artificial intelligence applications have gained traction in the field of cerebrovascular disease by assisting in the triage, classification, and prognostication of both ischemic and hemorrhagic stroke. The Caire ICH system aims to be the...