Ageing is the primary risk factor for many chronic, degenerative, and life-threatening disorders, yet the translational pipeline for geroprotective interventions remains comparatively sparse. Short‑lived, experimentally tractable models with conserve... read more
BACKGROUND: With the rising prevalence of primary total hip (THA) and knee arthroplasties (TKA), the number of periprosthetic fractures (PPF) is expected to increase. Myocardial infarction (MI) and cardiac arrest (CA) are devastating complications fo... read more
Journal of the American College of Radiology : JACR
Apr 9, 2026
INTRODUCTION: Radiology reports often contain complex medical jargon that can be difficult for patients to understand, especially those with limited English proficiency (LEP). With increased access to electronic health records, there is a need for pa... read more
BACKGROUND: Differentiating overt hepatic encephalopathy (OHE) from covert hepatic encephalopathy (CHE) remains challenging due to overlapping symptoms and the limitations of current grading tools. This study aimed to integrate quantitative susceptib... read more
Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
Apr 9, 2026
BACKGROUND: Sampling techniques have poor accuracy for classifying biliary strictures as benign or malignant. Previously, a cholangioscopy artificial intelligence (AI) outperformed sampling techniques based solely on analysis of previously recorded c... read more
BACKGROUND: The majority of studies that measure glenoid bone loss in the context of shoulder instability, are based on a sagittal image, termed the 'en-face' view, with the aid of best-fit circles. The en-face view has never been standardised in the... read more
INTRODUCTION: Feature selection plays a crucial role in improving predictive performance and interpretability in high-dimensional machine learning tasks. However, it is an NP-hard combinatorial optimization problem. Conventional heuristic or greedy a... read more
This study investigates practical design choices for Bayesian uncertainty quantification (UQ) in model-based deep learning (MoDL) for accelerated MRI reconstruction. Specifically, we examine where to introduce stochastic layers to capture epistemic u... read more
We developed an automatic self-enhancement-based perfusion mapping (SEPM) method to relatively map the microvascular perfusion level in contrast-enhanced magnetic resonance imaging (CE-MRI) into four categories: hyper-enhanced, isoenhanced, hypo-enha... read more
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