Latest AI and machine learning research in critical care for healthcare professionals.
Lumbar Spinal Stenosis (LSS) diagnosis remains a critical clinical challenge, with diagnosis heavily...
We propose FusionBERT, a novel multi-view visual fusion framework for image-3D multimodal retrieval....
Forecasting evolving clinical risks relies on intrinsic pathological dependencies rather than mere c...
Background: Extrauterine growth restriction (EUGR) is a common and clinically significant complicati...
Sepsis can lead to acute respiratory distress syndrome (ARDS) and is associated with a high mortalit...
The rapid advancement of AI research automation systems--including AI Scientist, data-to-paper, and ...
Cardiac surgery patients experience rapidly evolving hemodynamics in early post-operative period req...
Large Language Models achieve impressive accuracy on medical benchmarks that present clinical inform...
Existing multi-view crowd counting and localization methods are evaluated under relatively small sce...
Miscalibrated confidence scores are a practical obstacle to deploying AI in clinical settings. A mod...
Recent works have shown that Multimodal Large Language Models (MLLMs) are highly vulnerable to hidde...
Subject-driven image generation is increasingly expected to support fine-grained control over multip...
A precise spatial delivery of the radiation dose is crucial for the treatment success in radiotherap...
Diffusion-based text-to-image generation has advanced significantly, yet customizing scenes with mul...
Recognition of respiratory distress through visual inspection is a life saving clinical skill. Clini...
Accurate clinical triage is critical for optimizing decision-making and resource allocation during i...
The basic computational unit of the brain has long been defined as the neuron. However, mounting evi...
Background: Diffusion MRI (dMRI) is widely used to assess microstructural abnormalities in multiple ...
Objective: To evaluate a ranking approach for emergency department (ED) waiting room prioritization ...
Background: This study aims to develop and validate federated learning models for predicting major p...
As multi-agent AI systems are increasingly deployed in real-world settings - from automated customer...