Cardiovascular and interventional radiology
38530394
PURPOSE: The purpose of this study is to evaluate the efficacy of an artificial intelligence (AI) model designed to identify active bleeding in digital subtraction angiography images for upper gastrointestinal bleeding.
BACKGROUND: Renal artery pseudoaneurysm following partial nephrectomy is a rare entity, the incidence of this entity is more common following penetrating abdominal injuries, percutaneous renal interventions such as percutaneous nephrostomy(PCN) or Pe...
Cerebral aneurysm is a life-threatening condition, which requires high precision during the neurosurgical procedures. Increasing progress of evaluating modern devices in medicine have led to common usage of robotic systems in many fields, including c...
Cardiovascular engineering and technology
38782877
PURPOSE: To enhance the performance of machine learning (ML) models for the post-embolization recanalization of cerebral aneurysms, we evaluated the impact of hemodynamic feature derivation and selection method on six ML algorithms.
Cardiovascular and interventional radiology
38896298
PURPOSE: This study leverages pre-procedural data and machine learning (ML) techniques to predict outcomes at one year following prostate artery embolization (PAE).
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039575
This study presents an innovative method to increase the accuracy of coil selection for treating cerebral aneurysms, leveraging advanced image analysis and machine learning models. We examined 273 cases of saccular cerebral aneurysms treated at The J...
OBJECTIVES: To investigate the usefulness of super-resolution deep learning reconstruction (SR-DLR) with cardiac option in the assessment of image quality in patients with stent-assisted coil embolization, coil embolization, and flow-diverting stent ...
Journal of vascular and interventional radiology : JVIR
39638087
PURPOSE: To develop a machine learning algorithm to improve hepatic resection selection for patients with metastatic colorectal cancer (CRC) by predicting post-portal vein embolization (PVE) outcomes.
OBJECTIVE: This study was to explore the factors associated with prolonged hospital length of stay (LOS) in patients with intracranial aneurysms (IAs) undergoing endovascular interventional embolization and construct prediction model machine learning...