Physical and engineering sciences in medicine
38294678
CT angiography prior to endovascular aortic surgery is the standard non-invasive imaging method for evaluation of aortic dimensions and access sites. A detailed report is crucial to a proper planning. We assessed Artificial Intelligence (AI)-algorith...
The journal of trauma and acute care surgery
38548696
BACKGROUND: The optimal management of blunt thoracic aortic injury (BTAI) remains controversial, with experienced centers offering therapy ranging from medical management to TEVAR. We investigated the utility of a machine learning (ML) algorithm to d...
Cardiovascular and interventional radiology
38512351
PURPOSE: The LIBERTY® Robotic System is a miniature, single-use device designed to facilitate remote-controlled navigation to intravascular targets. We aim to evaluate the robot's performance to manipulate a range of microguidewires and microcatheter...
PURPOSE: This study aimed to construct a predictive model integrating deep learning-derived radiomic features from computed tomography angiography (CTA) and clinical biomarkers to forecast postoperative adverse events (AEs) in patients with acute unc...
Journal of the American Heart Association
38639373
BACKGROUND: Lower extremity endovascular revascularization for peripheral artery disease carries nonnegligible perioperative risks; however, outcome prediction tools remain limited. Using machine learning, we developed automated algorithms that predi...
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...
Physical and engineering sciences in medicine
38696098
To predict endoleaks after thoracic endovascular aneurysm repair (TEVAR) we submitted patient characteristics and vessel features observed on pre- operative computed tomography angiography (CTA) to machine-learning. We evaluated 1-year follow-up CT s...
BACKGROUND: Identification of futile recanalisation following endovascular therapy (EVT) in patients with acute ischaemic stroke is both crucial and challenging. Here, we present a novel risk stratification system based on hybrid machine learning met...
BACKGROUND: Deep learning using clinical and imaging data may improve pre-treatment prognostication in ischemic stroke patients undergoing endovascular thrombectomy (EVT).
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 ...