Latest AI and machine learning research in atherosclerosis for healthcare professionals.
PURPOSE: Autonomous systems in mechanical thrombectomy (MT) hold promise for reducing procedure times, minimizing radiation exposure, and enhancing patient safety. However, current reinforcement learning (RL) methods only reach the carotid arteries, are not generalizable to other patient vasculatures, and do not consider safety. We propose a safe dual-device RL algorithm that can navigate beyond t...
Deep learning has been used extensively for medical image analysis applications, assuming the training and test data adhere to the same probability distributions. However, a common challenge arises when dealing with medical images generated by different systems or even the same system with varying parameter settings. Such images often contain diverse textures and noise patterns, violating the assu...
Personalized nutrition programs enhanced with artificial intelligence (AI)-based tools hold promising potential for the development of healthy and su...
BACKGROUND: Coronary plaque features are imaging biomarkers of cardiovascular risk, but less is known about sex-specific patterns in their prognostic ...
The aim of this study was to establish the optimal prediction model by comparing the prediction effect of 6 kinds of prediction models containing bioc...
This article aimed to explore topological uncertainty in medical imaging, particularly in assessing coronary artery calcification using artificial int...
This study explores the development of a deep learning model using a neck-wearable piezoelectric sensor to accurately distinguish severe sleep apnea s...
Numerical simulations of fluid dynamics in tube-like structures are important to biomedical research to model flow in blood vessels and airways. It is...
Hand-foot skin reaction (HFSR) is a common adverse effect of vascular endothelial growth factor receptor (VEGFR) inhibitors that significantly impacts...
Coagulation within blood vessels is a major cause of cardiovascular disease and global mortality, highlighting the urgent need for effective anticoagu...
Abdominal aortic aneurysm (AAA) is a life-threatening disorder with limited therapeutic options. Neutrophil extracellular traps (NETs) are formed by a...
OBJECTIVE: Metabolic - associated fatty liver disease (MAFLD) is a common hepatic disorder with increasing prevalence, and early detection remains ina...
BACKGROUND: Neurointerventionalists must pay close attention to multiple devices on multiple screens simultaneously, which can lead to oversights and ...
PURPOSE: Utilizing artificial intelligence (AI) technology for the segmentation of plaques on ultrasound images to evaluate the stability of carotid a...
BACKGROUND: Surrogate insulin resistance (IR) indices are simpler and more practical alternatives to insulin-based IR indicators for clinical use. Thi...
OBJECTIVE: This study aims to develop a radiomics machine learning (ML) model that uses preoperative computed tomography angiography (CTA) data to pre...
Periodontal inflammation is a chronic condition affecting the tissues surrounding teeth. Initiated by dental plaque, it triggers an immune response le...
BACKGROUND: Intracranial aneurysm rupture is associated with high mortality and disability rates. Early detection is crucial, but increasing diagnosti...
Every year, Coronary Artery Disease (CAD) claims lives of over a million people. CAD occurs when the coronary arteries, responsible for supplying oxyg...
The study of type 2 diabetes mellitus (T2DM) pathophysiology relies mainly on the use of animal models, the most common of which involves the consumpt...