Atherosclerosis

Robotic Interventional Neuroradiology: Progress, Challenges, and Future Prospects.

Advances in robotic technology have improved standard techniques in numerous surgical and endovascular specialties, offering more precision, control, and better patient outcomes. Robotic-assisted interventional neuroradiology is an emerging field at the intersection of interventional neuroradiology and biomedical robotics. Endovascular robotics can automate maneuvers to reduce procedure times and ...

A systematic review on intracranial aneurysm and hemorrhage detection using machine learning and deep learning techniques.

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, however, the real hazard occurs when an aneurysm ruptures and results in a cerebral hemorrhage known as a subarachnoid hemorrhage. The objective is to st...

Unsupervised deep learning-based displacement estimation for vascular elasticity imaging applications.

. Arterial wall stiffness can provide valuable information on the proper function of the cardiovascular system. Ultrasound elasticity imaging techniqu...

Comparing the performance of machine learning and conventional models for predicting atherosclerotic cardiovascular disease in a general Chinese population.

BACKGROUND: Accurately predicting the risk of atherosclerotic cardiovascular disease (ASCVD) is crucial for implementing individualized prevention str...

Impact of Additional Administration of von Willebrand Factor Concentrates to Thrombocyte Transfusion in Perioperative Bleeding in Cardiac Surgery.

BACKGROUND: Von Willebrand factor (vWF) is an important part of blood coagulation since it binds platelets to each other and to endothelial cells. In ...

Computed Tomography 2.0: New Detector Technology, AI, and Other Developments.

Computed tomography (CT) dramatically improved the capabilities of diagnostic and interventional radiology. Starting in the early 1970s, this imaging ...

Accelerated Measurement of Carotid Plaque Volume Using Artificial Intelligence Enhanced 3D Ultrasound.

BACKGROUND: Carotid plaque volume (CPV) can be measured by 3D ultrasound and may be a better predictor of stroke than stenosis, but analysis time limi...

Rapid and stain-free quantification of viral plaque via lens-free holography and deep learning.

A plaque assay-the gold-standard method for measuring the concentration of replication-competent lytic virions-requires staining and usually more than...

USING CONVOLUTIONAL NEURAL NETWORK-BASED SEGMENTATION FOR IMAGE-BASED COMPUTATIONAL FLUID DYNAMICS SIMULATIONS OF BRAIN ANEURYSMS: INITIAL EXPERIENCE IN AUTOMATED MODEL CREATION.

"Image-based" computational fluid dynamics (CFD) simulations provide insights into each patient's hemodynamic environment. However, current standard p...

Dataset dependency of low-density lipoprotein-cholesterol estimation by machine learning.

OBJECTIVES: We evaluated the applicability of a machine learning-based low-density lipoprotein-cholesterol (LDL-C) estimation method and the influence...

Immediate Postoperative High Syndecan-1 is Associated with Short-Term Morbidity and Mortality After Robot-Assisted Esophagectomy: A Prospective Observational Study.

BACKGROUND: Disruption of the endothelial glycocalyx (EG) is associated with a poor prognosis in various clinical settings. This study aimed to determ...

Hardware-Efficient Scheme for Trailer Robot Parking by Truck Robot in an Indoor Environment with Rendezvous.

Autonomous grounded vehicle-based social assistance/service robot parking in an indoor environment is an exciting challenge in urban cities. There are...

Deep-learning-assisted and GPU-accelerated vector Doppler imaging with aliasing-resistant velocity estimation.

Vector flow imaging is a diagnostic ultrasound modality that is suited for the visualization of complex blood flow dynamics. One popular way of realiz...

AI-Driven sleep staging from actigraphy and heart rate.

Sleep is an important indicator of a person's health, and its accurate and cost-effective quantification is of great value in healthcare. The gold sta...

Neurosurgical skills analysis by machine learning models: systematic review.

Machine learning (ML) models are being actively used in modern medicine, including neurosurgery. This study aimed to summarize the current application...

From jeopardy champion to drug discovery; semantic similarity artificial intelligence.

We have employed artificial intelligence to streamline the small molecule drug screening pipeline and identified the cholesterol-reducing compound pro...

Comparative study of lipid nanoparticle-based mRNA vaccine bioprocess with machine learning and combinatorial artificial neural network-design of experiment approach.

To develop a combinatorial artificial-neural-network design-of-experiment (ANN-DOE) model, the effect of ionizable lipid, an ionizable lipid-to-choles...

Semi-Automated Data Curation from Biomedical Literature.

Data curation is a bottleneck for many informatics pipelines. A specific example of this is aggregating data from preclinical studies to identify nove...

Development and validation of a deep learning model for prediction of intracranial aneurysm rupture risk based on multi-omics factor.

OBJECTIVE: The clinical ability of radiomics to predict intracranial aneurysm rupture risk remains unexplored. This study aims to investigate the pote...

Can convolutional neural networks identify external carotid artery calcifications?

OBJECTIVE: We developed and evaluated the accuracy and reliability of a convolutional neural network (CNN) in detecting external carotid artery calcif...