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 …

Introduction Cerebrovascular diseases are known to cause significant morbidity and
mortality to the general population. In patients with cerebrovascular disease, prompt clinical …

Intracranial aneurysms are a common asymptomatic vascular pathology, the rupture of
which is a devastating event with a significant risk of morbidity and mortality. Aneurysm …

Background The rupture risk assessment of intracranial aneurysms (IAs) is clinically
relevant. How to accurately assess the rupture risk of IAs remains a challenge in clinical …

Background Intracranial aneurysm (IA) is a nodular protrusion of the arterial wall caused by
the localized abnormal enlargement of the lumen of a brain artery, which is the primary …

Purpose To evaluate the diagnostic efficacy of a developed artificial intelligence (AI) platform
incorporating deep learning algorithms for the automated detection of intracranial …

Traditional guidance for intracranial aneurysm (IA) management is dichotomized by rupture
status. Fundamental to ruptured aneurysm management is the detection and treatment of …

Background and Purpose: Precisely assessing the likelihood of an intracranial aneurysm
rupturing is critical for guiding clinical decision-making. The objective of this study is to …

Growing intracranial aneurysms pose a high risk of rupture, making the detection and
quantification of the growth crucial for timely treatment strategy adoption. In this paper we …

Purpose Subarachnoid haemorrhage is a potentially fatal consequence of intracranial
aneurysm rupture, however, it is difficult to predict if aneurysms will rupture. Prophylactic …