It is possible to identify unruptured intracranial aneurysms (UIA) using machine learning
(ML) algorithms, which can be a life-saving strategy, especially in high-risk populations. To …

Background: Hemodynamics plays a crucial role in the initiation, enlargement, and rupture
of intracranial aneurysms (IAs). This bibliometric analysis aimed to map the knowledge …

Purpose The study aimed to identify potential risk factors for aneurysm rupture by performing
a systematic review and meta-analysis. Materials and methods We systematically searched …

Cerebral aneurysms are a serious clinical challenge, with∼ half resulting in death or
disability. Treatment via endovascular coiling significantly reduces the chances of rupture …

Objectives To identify the morphologic and hemodynamic risk factor of mirror middle
cerebral artery (MCA) aneurysms. Methods We conducted a retrospective analysis of 40 …

Purpose Medical researchers deal with a large amount of patient data to improve future
treatment decisions and come up with new hypotheses. To facilitate working with a large …

Objective: The aim of this study is to perform specific hemodynamic simulations of idealized
abdominal aortic aneurysm (AAA) models with different diameters, curvatures and …

Background Computational fluid dynamics (CFD) simulations are a powerful tool for
studying cerebral aneurysms, capable of evaluating hemodynamics in a way that is …

Objectives To identify hemodynamic risk factors for intracranial aneurysm rupture and
establish a predictive model to aid evaluation. Methods We analyzed the hemodynamic …

Background Predicting rupture risk is important for aneurysm management. This research
aimed to develop and validate a nomogram model to forecast the rupture risk of posterior …