AIMC Topic: Aneurysm, Ruptured

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Revolutionizing Aneurysm detection: The role of artificial intelligence in reducing rupture rates.

Neurosurgical review Aug 1, 2024
Cerebral aneurysms, affecting 2-5% of the global population, are often asymptomatic and commonly located within the Circle of Willis. A recent study in Neurosurgical Review highlights a significant reduction in the annual rupture rates of unruptured ...
Humans Cerebral Angiography Aneurysm, Ruptured Intracranial Aneurysm Artificial Intelligence Machine Learning Subarachnoid Hemorrhage
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A comprehensive investigation of morphological features responsible for cerebral aneurysm rupture using machine learning.

Scientific reports Jul 9, 2024
Cerebral aneurysms are a silent yet prevalent condition that affects a significant global population. Their development can be attributed to various factors, presentations, and treatment approaches. The importance of selecting the appropriate treatme...
Aneurysm, Ruptured Intracranial Aneurysm Humans Aged Male Machine Learning Middle Aged Algorithms Female
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Deep learning-based cerebral aneurysm segmentation and morphological analysis with three-dimensional rotational angiography.

Journal of neurointerventional surgery Jan 12, 2024
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...
Aneurysm, Ruptured Intracranial Aneurysm Reproducibility of Results Humans Deep Learning Retrospective Studies Cerebral Angiography
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A systematic review on intracranial aneurysm and hemorrhage detection using machine learning and deep learning techniques.

Progress in biophysics and molecular biology Jul 25, 2023
The risk of discovering an intracranial aneurysm during the initial screening and follow-up screening are reported as around 11%, and 7% respectively (Zuurbie et al., 2023) to these mass effects, unruptured aneurysms frequently generate symptoms, how...
Humans Deep Learning Subarachnoid Hemorrhage Aneurysm, Ruptured Artificial Intelligence Machine Learning Reproducibility of Results Intracranial Aneurysm
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Development and validation of a deep learning model for prediction of intracranial aneurysm rupture risk based on multi-omics factor.

European radiology Apr 26, 2023
OBJECTIVE: The clinical ability of radiomics to predict intracranial aneurysm rupture risk remains unexplored. This study aims to investigate the potential uses of radiomics and explore whether deep learning (DL) algorithms outperform traditional sta...
Aneurysm, Ruptured Intracranial Aneurysm Retrospective Studies Deep Learning Multiomics Humans
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Deep learning-based semantic vessel graph extraction for intracranial aneurysm rupture risk management.

International journal of computer assisted radiology and surgery Jan 10, 2023
PURPOSE: Intracranial aneurysms are vascular deformations in the brain which are complicated to treat. In clinical routines, the risk assessment of intracranial aneurysm rupture is simplified and might be unreliable, especially for patients with mult...
Deep Learning Semantics Cerebral Angiography Aneurysm, Ruptured Humans Intracranial Aneurysm Risk Factors Risk Assessment
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Rupture risk prediction of cerebral aneurysms using a novel convolutional neural network-based deep learning model.

Journal of neurointerventional surgery Feb 9, 2022
BACKGROUND: Cerebral aneurysms should be treated before rupture because ruptured aneurysms result in serious disability. Therefore, accurate prediction of rupture risk is important and has been estimated using various hemodynamic factors.
Humans Aneurysm, Ruptured Neural Networks, Computer Intracranial Aneurysm Retrospective Studies Hemodynamics Deep Learning
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Machine Learning-Based Prediction of Small Intracranial Aneurysm Rupture Status Using CTA-Derived Hemodynamics: A Multicenter Study.

AJNR. American journal of neuroradiology Mar 4, 2021
BACKGROUND AND PURPOSE: Small intracranial aneurysms are being increasingly detected while the rupture risk is not well-understood. We aimed to develop rupture-risk models of small aneurysms by combining clinical, morphologic, and hemodynamic informa...
Intracranial Aneurysm Retrospective Studies Humans Hemodynamics Machine Learning Aneurysm, Ruptured
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A pilot study using a machine-learning approach of morphological and hemodynamic parameters for predicting aneurysms enhancement.

International journal of computer assisted radiology and surgery Jun 8, 2020
PURPOSE: The development of straightforward classification methods is needed to identify unstable aneurysms and rupture risk for clinical use. In this study, we aim to investigate the relative importance of geometrical, hemodynamic and clinical risk ...
Middle Aged Hemodynamics Pilot Projects Linear Models Stress, Mechanical Aneurysm, Ruptured Machine Learning Female Male Humans Intracranial Aneurysm
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Development and validation of machine learning prediction model based on computed tomography angiography-derived hemodynamics for rupture status of intracranial aneurysms: a Chinese multicenter study.

European radiology Apr 29, 2020
OBJECTIVES: To build models based on conventional logistic regression (LR) and machine learning (ML) algorithms combining clinical, morphological, and hemodynamic information to predict individual rupture status of unruptured intracranial aneurysms (...
Clinical Decision Rules China Adolescent Tomography, X-Ray Computed Logistic Models Machine Learning Humans Aged, 80 and over Female Male Cerebral Angiography Computer Simulation Neural Networks, Computer Young Adult Support Vector Machine Aged Middle Aged Aneurysm, Ruptured Retrospective Studies Adult Hemodynamics Intracranial Aneurysm Area Under Curve Computed Tomography Angiography
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