Neurosurgery

Applying artificial intelligence to longitudinal imaging analysis of vestibular schwannoma following radiosurgery.

Artificial intelligence (AI) has been applied with considerable success in the fields of radiology, ...

Path Planning of Unmanned Autonomous Helicopter Based on Human-Computer Hybrid Augmented Intelligence.

Unmanned autonomous helicopter (UAH) path planning problem is an important component of the UAH miss...

Does Robot Navigation and Intraoperative Computed Tomography Guidance Help with Percutaneous Endoscopic Lumbar Discectomy? A Match-Paired Study.

OBJECTIVE: To evaluate the efficacy and safety of robot-assisted percutaneous endoscopic lumbar disc...

Artificial Intelligence Technologies in Neurosurgery: a Systematic Literature Review Using Topic Modeling. Part II: Research Objectives and Perspectives.

UNLABELLED: The current increase in the number of publications on the use of artificial intelligence...

Ultrashort echo time time-spatial labeling inversion pulse magnetic resonance angiography with denoising deep learning reconstruction for the assessment of abdominal visceral arteries.

Current contrast-enhanced magnetic resonance angiography (MRA) and non-contrast-enhanced balanced st...

Predicting the Individual Treatment Effect of Neurosurgery for Patients with Traumatic Brain Injury in the Low-Resource Setting: A Machine Learning Approach in Uganda.

Traumatic brain injury (TBI) disproportionately affects low- and middle-income countries (LMICs). In...

Fully automated detection and segmentation of intracranial aneurysms in subarachnoid hemorrhage on CTA using deep learning.

In aneurysmal subarachnoid hemorrhage (aSAH), accurate diagnosis of aneurysm is essential for subseq...

Fully automatic volume segmentation of infrarenal abdominal aortic aneurysm computed tomography images with deep learning approaches versus physician controlled manual segmentation.

OBJECTIVE: Imaging software has become critical tools in the diagnosis and decision making for the t...

Global adoption of robotic technology into neurosurgical practice and research.

Recent technological advancements have led to the development and implementation of robotic surgery ...

A clinically applicable deep-learning model for detecting intracranial aneurysm in computed tomography angiography images.

Intracranial aneurysm is a common life-threatening disease. Computed tomography angiography is recom...

Attitudes of the Surgical Team Toward Artificial Intelligence in Neurosurgery: International 2-Stage Cross-Sectional Survey.

BACKGROUND: Artificial intelligence (AI) has the potential to disrupt how we diagnose and treat pati...

Predictive score for complete occlusion of intracranial aneurysms treated by flow-diverter stents using machine learning.

BACKGROUND: Complete occlusion of an intracranial aneurysm (IA) after the deployment of a flow-diver...

Automated Aneurysm Detection: Emerging from the Shallow End of the Deep Learning Pool.

Deep Learning for Detecting Cerebral Aneurysms with CT Angiography.

Background Cerebral aneurysm detection is a challenging task. Deep learning may become a supportive ...

Artificial Intelligence in Neurosurgery: a Systematic Review Using Topic Modeling. Part I: Major Research Areas.

UNLABELLED: In recent years, the number of scientific publications on artificial intelligence (AI), ...

Artificial Intelligence and Deep Learning in Neuroradiology: Exploring the New Frontier.

There have been many recently published studies exploring machine learning (ML) and deep learning ap...

A generic physics-informed neural network-based constitutive model for soft biological tissues.

Constitutive modeling is a cornerstone for stress analysis of mechanical behaviors of biological sof...

Radiomic Model for Distinguishing Dissecting Aneurysms from Complicated Saccular Aneurysms on high-Resolution Magnetic Resonance Imaging.

OBJECTIVE: To build radiomic model in differentiating dissecting aneurysm (DA) from complicated sacc...

Deep learning-based lumbosacral reconstruction for difficulty prediction of percutaneous endoscopic transforaminal discectomy at L5/S1 level: A retrospective cohort study.

BACKGROUND: Deep learning has been validated as a promising technique for automatic segmentation and...

Prediction, pattern recognition and modelling of complications post-endovascular infra renal aneurysm repair by artificial intelligence.

OBJECTIVES: The study evaluates the plausibility and applicability of prediction, pattern recognitio...

Machine learning in neurosurgery: a global survey.

BACKGROUND: Recent technological advances have led to the development and implementation of machine ...