Latest AI and machine learning research in intensivists for healthcare professionals.
Precise prognostication in acute brain injury is limited by a lack of reliable biomarkers of consciousness available to clinicians at the bedside. The ABCD framework is a method of classifying resting-state clinical EEG into categories that reflect levels of thalamocortical network function. ABCD classifications in the intensive care unit (ICU) have been shown to provide diagnostic and prognostic ...
BackgroundVentilator-associated pneumonia (VAP) is the most frequent nosocomial infection in critical care, affecting 20-36% of mechanically ventilated patients. Early prediction is hampered by the absence of a reliable, objective diagnostic standard. We developed ADVISE (Automated Dudley Ventilation Infection Series Evaluation), a machine learning model to predict physiological deterioration cons...
General-purpose models often struggle to reliably identify and understand real-world multimodal risks, largely due to the inherent multimodal adversar...
We prove a single algebraic mixed coincidence identity that unifies a broad swath of information-theoretic variational results. For any family of prio...
Recent breakthroughs in 3D generation have advanced notably with the development of text-to-image diffusion model. However, existing methods remain tw...
Rapid and accurate pathogen identification is crucial for the clinical management of infectious diseases, particularly sepsis and severe respiratory i...
Can one graph represent every kind of LLM agent's run? A trace records what each step did, never what it relied on, the state it read, and the results...
Modern Referring Image Segmentation (RIS) systems generate multiple candidate masks per expression but rely on a simple heuristic--typically the argma...
Burst suppression (BS) is a clinically relevant electroencephalographic (EEG) pattern used to monitor sedation depth and brain activity in critically ...
Delirium is a common and serious complication in the Intensive Care Unit (ICU), associated with increased morbidity, prolonged hospital stays, and hig...
Generating adversarial driving scenarios is critical for evaluating and improving autonomous vehicle decision-making systems in simulation. Recent app...
AI systems deployed in legal workflows hallucinate at rates that aggregate metrics report at ~52%, but this average conceals where errors concentrate ...
Multi-subject reference-based image generation requires jointly preserving multiple human identities, binding per-person objects and fashion items, an...
Aim: The global population of older adults is growing, and older age is linked to higher bleeding risk. Although guidelines discourage aspirin for pri...
Personalized medicine in acute ischemic stroke requires moving beyond average treatment effects (ATE) to individualized treatment effect (ITE) estimat...
High-frequency physiological monitoring in ICUs can identify impending deterioration hours before clinical recognition yet extracting reliable early-w...
Multi-task vehicle routing problems play a critical role in enhancing efficiency across various industries and service sectors. These problems consist...
Image generation models now produce high-quality static images, yet their ability to represent how a visual world changes over time remains poorly und...
The emergence of reasoning multimodal large language models (MLLMs), which generate explicit chain-of-thought (CoT) reasoning before producing answers...
In recent years, unified multimodal models (UMMs) have emerged to support both understanding and generation within a single framework. Mastering dynam...