Purpose Unruptured cerebral aneurysms pose a dilemma for physicians who need to weigh
the risk of a devastating subarachnoid hemorrhage against the risk of surgery or …

Purpose Incidental aneurysms pose a challenge to physicians who need to decide whether
or not to treat them. A statistical model could potentially support such treatment decisions …

Objectives To build models based on conventional logistic regression (LR) and machine
learning (ML) algorithms combining clinical, morphological, and hemodynamic information …

Background: Assessment of cerebral aneurysm rupture risk is an important task, but it
remains challenging. Recent works applying machine learning to rupture risk evaluation …

OBJECTIVE Incidental aneurysms pose a challenge for physicians, who need to weigh the
rupture risk against the risks associated with treatment and its complications. A statistical …

Objective: The aim of the present study is to investigate the potential morphological and
hemodynamic risk factors related to intracranial aneurysms (IAs) rupture and establish a …

BACKGROUND AND PURPOSE: Computational fluid dynamics has become a popular tool
for studying intracranial aneurysm hemodynamics, demonstrating success for retrospectively …

Purpose To construct a classification model of rupture status and to clarify the importance of
morphologic variables and hemodynamic parameters on rupture status by applying a …

BACKGROUND AND PURPOSE: Small intracranial aneurysms are being increasingly
detected while the rupture risk is not well-understood. We aimed to develop rupture-risk …

Object The goal of this study was to establish a biomathematical model to accurately predict
the probability of aneurysm rupture. Biomathematical models incorporate various physical …