BACKGROUND AND OBJECTIVES: Intracranial atherosclerotic stenosis of a major intracranial artery is the common cause of ischemic stroke. We evaluate the feasibility of using deep learning to automatically detect intracranial arterial steno-occlusive l...
Computational and mathematical methods in medicine
Aug 18, 2021
Carotid plaque echogenicity in ultrasound images has been found to be closely correlated with the risk of stroke in atherosclerotic patients. The automatic and accurate classification of carotid plaque echogenicity is of great significance for clinic...
Biomechanics and modeling in mechanobiology
Jul 31, 2021
This study presents an application of machine learning (ML) methods for detecting the presence of stenoses and aneurysms in the human arterial system. Four major forms of arterial disease-carotid artery stenosis (CAS), subclavian artery stenosis (SAS...
OBJECTIVE: Investigation of asymptomatic carotid stenosis treatment is hindered by the lack of a contemporary population-based disease cohort. We describe the use of natural language processing (NLP) to identify stenosis in patients undergoing caroti...
BACKGROUND: Lower extremity arterial Doppler (LEAD) and duplex carotid ultrasound studies are used for the initial evaluation of peripheral arterial disease and carotid stenosis. However, intra- and inter-laboratory variability exists between interpr...
Cardiovascular and interventional radiology
Jan 14, 2021
PURPOSE: Endovascular robotics is an emerging technology within the developing field of medical robotics. This was a prospective evaluation to assess safety and feasibility of robotic-assisted carotid artery stenting.
The international journal of cardiovascular imaging
Jan 9, 2021
Visual or manual characterization and classification of atherosclerotic plaque lesions are tedious, error-prone, and time-consuming. The purpose of this study is to develop and design an automated carotid plaque characterization and classification sy...
The international journal of cardiovascular imaging
Nov 12, 2020
Machine learning (ML)-based algorithms for cardiovascular disease (CVD) risk assessment have shown promise in clinical decisions. However, they usually predict binary events using only conventional risk factors. Our overall goal was to develop the "m...
BACKGROUND: This study aimed to establish and validate a machine learning-based model for the prediction of early phase postoperative hypertension (EPOH) requiring the administration of intravenous vasodilators after carotid endarterectomy (CEA).
Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions
May 5, 2020
The use of robotic assistance in endovascular interventions may facilitate smoother procedures with fewer device manipulations, improve precision and accuracy of device deployment, and reduce exposure to fluoroscopic radiation. We used the CorPath GR...
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