Latest AI and machine learning research in medical education for healthcare professionals.
Text-rich visual inputs require models that can read, retrieve, and compress language directly in pi...
Background. Cardiovascular-outcomes trials are lengthy, costly, and associated with substantial unce...
Federated learning (FL) has emerged as a key approach for training models across decentralized data,...
Imputing physiological time series (arterial blood pressure, blood glucose, etc.) is essential for a...
Self-supervised pretraining on remote sensing imagery typically treats all samples as equally inform...
Myocardial scar segmentation from single-stack late gadolinium-enhanced cardiac magnetic resonance (...
Large-scale image generation has benefited from advances in data scale, quality, rebalancing, and re...
While vision-language models dominate medical representation learning, unstructured text lacks the d...
IoT firmware vulnerability detection remains challenging due to heterogeneous firmware ecosystems, r...
Robust navigation policies for autonomous agents must generalize across continuously varying environ...
Many critical reasoning tasks, including clinical diagnosis, legal judgment, and industrial fault di...
Design campaigns in chemistry, materials science, and machine learning share a bottleneck: determini...
Generative video compositing, which involves inserting external assets seamlessly into existing vide...
Image-based reconstruction aims to recover three-dimensional geometry from images. Recent advances h...
Medical world models offer a framework for extending medical artificial intelligence beyond static p...
Medical image visualization requires volumetric rendering algorithms that preserve anatomical fideli...
Preformed and de novo antibodies against donor human leukocyte antigen (HLA) antigens remain a major...
Medical multimodal large language models (MLLMs) are increasingly expected to perform complex image ...
Significance: Computational modeling and the use of simulation software tools are essential for biom...
Neural simulation-based inference enables parameter estimation for complex models, but typically req...
Physical simulations that predict the behavior of urban disasters, such as climate-related flooding,...