Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.
PURPOSE: As artificial intelligence (AI) becomes increasingly integrated into financial decision-making, concerns about responsibility attribution in human-AI collaboration have intensified. This study examines how AI trust relates to the displacement of responsibility. METHODS: Drawing on automation trust theory and moral disengagement theory, we propose a mediation model in which decision delega...
Accurate automated segmentation of Lumbar Spine Structures (LSS) in Magnetic Resonance Imaging (MRI) is important for effective diagnosis and treatment planning. However, most current methods encounter a trade-off between segmentation precision and computational efficiency. In particular, several methods fall short in modelling the intricate multi-scale anatomical details and subtle boundary trans...
PURPOSE: Indocyanine green (ICG) fluorescence imaging is increasingly used for intraoperative bowel perfusion assessment in neonatal surgery. However,...
Liver tumor segmentation from CT images remains challenging due to large variations in lesion scale, blurred boundaries, low tissue contrast, and the ...
BACKGROUND: Unlicensed medical practices (UMPs) pose a substantial threat to patient safety and public health, but their clandestine nature makes them...
Burn care frequently relies on extensive documentation, including graphic photographic images and detailed clinical records. While these materials are...
The dynamic environment of medicine, particularly in settings such as the Emergency Department, challenges physicians with an influx of patient data a...
Accurate detection of overhanging dental restorations on bitewing radiographs is clinically important but remains challenging due to subtle marginal d...
The aim of this study is to comprehensively examine the evolution of artificial intelligence (AI), specifically large language models (LLMs), in the f...
Artificial intelligence and data-driven models are changing hepatology, but expert clinical judgment remains essential. Liver diseases are complex and...
INTRODUCTION: Lung cancer is commonly associated with smoking. However, if considered separately, lung cancer in never-smokers (LCINS) is the seventh ...
In medical image segmentation, inherent boundary ambiguity, tissue overlap, and weak intensity gradients often produce blurred or discontinuous edges,...
The rapid integration of generative artificial intelligence (AI) tools into higher education has intensified conversations regarding usefulness, ethic...
Atomic structures of a Lu-segregated grain boundary (GB) in α-Al2O3 are identified using hybrid Monte Carlo and molecular dynamics (MCMD) simulations ...
OBJECTIVE: Fetal head circumference (HC) measurement is a routine and indispensable examination during pregnancy, closely associated with fetal health...
INTRODUCTION: The use of artificial intelligence (AI) in the scientific process is advancing at a remarkable speed, thanks to continued innovations in...
OBJECTIVES: To predict abnormal pulmonary artery hemodynamics caused by ventricular septal defect (VSD) using Physics-Informed Neural Networks (PINN) ...
The biobank is a functional unit that facilitates and improves research by storing biological samples and associated data. As such, it is a key resour...
In the molecular design of high-performance materials, the physical properties (y) of chemical structures generated virtually by a computer is predict...
Brain tumor segmentation requires precise delineation of hierarchical structures from multi-sequence MRI. However, existing deep learning methods prim...