AI Medical Compendium Journal:
Journal of neurointerventional surgery

Showing 1 to 10 of 31 articles

Machine learning for clinical outcome prediction in cerebrovascular and endovascular neurosurgery: systematic review and meta-analysis.

Journal of neurointerventional surgery
BACKGROUND: Machine learning (ML) may be superior to traditional methods for clinical outcome prediction. We sought to systematically review the literature on ML for clinical outcome prediction in cerebrovascular and endovascular neurosurgery.

Deep learning-based model for difficult transfemoral access prediction compared with human assessment in stroke thrombectomy.

Journal of neurointerventional surgery
BACKGROUND: In mechanical thrombectomy (MT), extracranial vascular tortuosity is among the main determinants of procedure duration and success. Currently, no rapid and reliable method exists to identify the anatomical features precluding fast and sta...

Real time artificial intelligence assisted carotid artery stenting: a preliminary experience.

Journal of neurointerventional surgery
BACKGROUND: Neurointerventionalists must pay close attention to multiple devices on multiple screens simultaneously, which can lead to oversights and complications. Artificial intelligence (AI) has potential application in recognizing and monitoring ...

Assessing the clinical reasoning of ChatGPT for mechanical thrombectomy in patients with stroke.

Journal of neurointerventional surgery
BACKGROUND: Artificial intelligence (AI) has become a promising tool in medicine. ChatGPT, a large language model AI Chatbot, shows promise in supporting clinical practice. We assess the potential of ChatGPT as a clinical reasoning tool for mechanica...

Automated catheter segmentation and tip detection in cerebral angiography with topology-aware geometric deep learning.

Journal of neurointerventional surgery
BACKGROUND: Visual perception of catheters and guidewires on x-ray fluoroscopy is essential for neurointervention. Endovascular robots with teleoperation capabilities are being developed, but they cannot 'see' intravascular devices, which precludes a...

Deep learning-based cerebral aneurysm segmentation and morphological analysis with three-dimensional rotational angiography.

Journal of neurointerventional surgery
BACKGROUND: The morphological assessment of cerebral aneurysms based on cerebral angiography is an essential step when planning strategy and device selection in endovascular treatment, but manual evaluation by human raters only has moderate interrate...

The perils and promises of generative artificial intelligence in neurointerventional surgery.

Journal of neurointerventional surgery
Generative artificial intelligence (AI) holds great promise in neurointerventional surgery by providing clinicians with powerful tools for improving surgical precision, accuracy of diagnoses, and treatment planning. However, potential perils include ...

Clinical evaluation of a deep-learning model for automatic scoring of the Alberta stroke program early CT score on non-contrast CT.

Journal of neurointerventional surgery
BACKGROUND: Automated measurement of the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) can support clinical decision making. Based on a deep learning algorithm, we developed an automated ASPECTS scoring system (Heuron ASPECTS) and ...