AIMC Topic: Endovascular Procedures
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Imaging analysis using Artificial Intelligence to predict outcomes after endovascular aortic aneurysm repair: protocol for a retrospective cohort study.
BMJ open
Jul 16, 2025
INTRODUCTION: Endovascular aortic aneurysm repair (EVAR) requires long-term surveillance to detect and treat postoperative complications. However, prediction models to optimise follow-up strategies are still lacking. The primary objective of this stu...
Cerebral aneurysm surgical training in the neuroendovascular era and its impact on the production of comfortable aneurysm surgeons.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Jun 5, 2025
BACKGROUND: The increasing use of endovascular techniques has greatly decreased the number of intracranial aneurysms treated with open surgery. The objective of this study is to quantify chief residents' experience and comfort level with clipping of ...
Benchmarking reinforcement learning algorithms for autonomous mechanical thrombectomy.
International journal of computer assisted radiology and surgery
Apr 29, 2025
PURPOSE: Mechanical thrombectomy (MT) is the gold standard for treating acute ischemic stroke. However, challenges such as operator radiation exposure, reliance on operator experience, and limited treatment access remain. Although autonomous robotics...
Predicting Long-Term Survival after Endovascular Aneurysm Repair Using Machine Learning-Based Decision Tree Analysis.
Vascular and endovascular surgery
Mar 24, 2025
ObjectiveEndovascular aneurysm repair (EVAR) has become a preferred method for treating abdominal aortic aneurysms (AAA) due to its minimally invasive approach. However, identifying factors that influence long-term patient outcomes is crucial for imp...
Aged
Aged, 80 and over
Male
Middle Aged
Retrospective Studies
Clinical Decision-Making
Female
Risk Factors
Predictive Value of Tests
Aortic Aneurysm, Abdominal
Blood Vessel Prosthesis Implantation
Endovascular Procedures
Endovascular Aneurysm Repair
Risk Assessment
Time Factors
Treatment Outcome
Decision Trees
Humans
Machine Learning
Decision Support Techniques
Development of an Intuitive Interface With Haptic Enhancement for Robot-Assisted Endovascular Intervention.
IEEE transactions on haptics
Mar 21, 2025
Robot-assisted endovascular intervention has the potential to reduce radiation exposure to surgeons and enhance outcomes of interventions. However, the success and safety of endovascular interventions depend on surgeons' ability to accurately manipul...
Real time artificial intelligence assisted carotid artery stenting: a preliminary experience.
Journal of neurointerventional surgery
Mar 17, 2025
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 ...
A computed tomography angiography-based radiomics model for prognostic prediction of endovascular abdominal aortic repair.
International journal of cardiology
Mar 14, 2025
OBJECTIVE: This study aims to develop a radiomics machine learning (ML) model that uses preoperative computed tomography angiography (CTA) data to predict the prognosis of endovascular aneurysm repair (EVAR) for abdominal aortic aneurysm (AAA) patien...
Using Machine Learning to Predict Outcomes Following Thoracic and Complex Endovascular Aortic Aneurysm Repair.
Journal of the American Heart Association
Mar 3, 2025
BACKGROUND: Thoracic endovascular aortic repair (TEVAR) and complex endovascular aneurysm repair (EVAR) are complex procedures that carry a significant risk of complications. While risk prediction tools can aid in clinical decision making, they remai...
Deep Learning-Assisted Diagnosis of Malignant Cerebral Edema Following Endovascular Thrombectomy.
Academic radiology
Feb 28, 2025
BACKGROUND: Malignant cerebral edema (MCE) is a significant complication following endovascular thrombectomy (EVT) in the treatment of acute ischemic stroke. This study aimed to develop and validate a deep learning-assisted diagnosis model based on t...
Deep learning on pre-procedural computed tomography and clinical data predicts outcome following stroke thrombectomy.
Journal of neurointerventional surgery
Feb 14, 2025
BACKGROUND: Deep learning using clinical and imaging data may improve pre-treatment prognostication in ischemic stroke patients undergoing endovascular thrombectomy (EVT).
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