Neurosurgery

Off-Label use of Woven EndoBridge device for intracranial brain aneurysm treatment: Modeling of occlusion outcome.

INTRODUCTION: The Woven EndoBridge (WEB) device is emerging as a novel therapy for intracranial aneu...

Deep learning for intracranial aneurysm segmentation using CT angiography.

This study aimed to employ a two-stage deep learning method to accurately detect small aneurysms (4-...

A microdiscectomy surgical video annotation framework for supervised machine learning applications.

PURPOSE: Lumbar discectomy is among the most common spine procedures in the US, with 300,000 procedu...

Apple Intelligence in neurosurgery.

With the current artificial intelligence (AI) boom, new innovative and accessible applications requi...

Automated Method for Intracranial Aneurysm Classification Using Deep Learning.

Intracranial aneurysm (IA) is now a common term closely associated with subarachnoid hemorrhage. IA ...

Assessing accuracy and consistency in intracranial aneurysm sizing: human expertise vs. artificial intelligence.

Intracranial aneurysms (IAs) are a common vascular pathology and are associated with a risk of ruptu...

A comprehensive investigation of morphological features responsible for cerebral aneurysm rupture using machine learning.

Cerebral aneurysms are a silent yet prevalent condition that affects a significant global population...

Artificial intelligence-driven multiomics predictive model for abdominal aortic aneurysm subtypes to identify heterogeneous immune cell infiltration and predict disease progression.

BACKGROUND: Abdominal aortic aneurysm (AAA) poses a significant health risk and is influenced by var...

Machine Learning Based Prediction of Post-operative Infrarenal Endograft Apposition for Abdominal Aortic Aneurysms.

OBJECTIVE: Challenging infrarenal aortic neck characteristics have been associated with an increased...

Classification, detection, and segmentation performance of image-based AI in intracranial aneurysm: a systematic review.

BACKGROUND: The detection and management of intracranial aneurysms (IAs) are vital to prevent life-t...

7 T and beyond: toward a synergy between fMRI-based presurgical mapping at ultrahigh magnetic fields, AI, and robotic neurosurgery.

Presurgical evaluation with functional magnetic resonance imaging (fMRI) can reduce postsurgical mor...

Text-to-video generative artificial intelligence: sora in neurosurgery: correspondence.

Artificial Intelligence Based Methods to Enhance Analysis of Non-Contrast Computed Tomography in Patients with Aortic Aneurysm.

Integrated analysis of single-cell sequencing and machine learning identifies a signature based on monocyte/macrophage hub genes to analyze the intracranial aneurysm associated immune microenvironment.

Monocytes are pivotal immune cells in eliciting specific immune responses and can exert a significan...

Text-to-video generative artificial intelligence: sora in neurosurgery.

Artificial intelligence (AI) has increased in popularity in neurosurgery, with recent interest in ge...

URCA: Uncertainty-based region clipping algorithm for semi-supervised medical image segmentation.

BACKGROUND AND OBJECTIVE: Training convolutional neural networks based on large amount of labeled da...

Improving intracranial aneurysms image quality and diagnostic confidence with deep learning reconstruction in craniocervical CT angiography.

BACKGROUND: The diagnostic impact of deep learning computed tomography (CT) reconstruction on intrac...

Assessing the Impact of an Artificial Intelligence-Based Model for Intracranial Aneurysm Detection in CT Angiography on Patient Diagnosis and Outcomes (IDEAL Study)-a protocol for a multicenter, double-blinded randomized controlled trial.

BACKGROUND: This multicenter, double-blinded, randomized controlled trial (RCT) aims to assess the i...

Dissatisfaction-considered waiting time prediction for outpatients with interpretable machine learning.

Long waiting time in outpatient departments is a crucial factor in patient dissatisfaction. We aim t...

Impact Exploration of Spatiotemporal Feature Derivation and Selection on Machine Learning-Based Predictive Models for Post-Embolization Cerebral Aneurysm Recanalization.

PURPOSE: To enhance the performance of machine learning (ML) models for the post-embolization recana...

Machine learning models on a web application to predict short-term postoperative outcomes following anterior cervical discectomy and fusion.

BACKGROUND: The frequency of anterior cervical discectomy and fusion (ACDF) has increased up to 400%...