Latest AI and machine learning research in product alert for healthcare professionals.
The assessment of planktonic standing stocks and microorganism structures is critical for understanding upper ocean biological processes. Currently, autonomous underwater vehicles (AUVs) equipped with in-situ optical imaging and artificial intelligence (AI) methods offer a promising solution for persistent surveillance, mapping and monitoring of planktonic life. However, current AI methods often l...
Error monitoring allows for detecting mistakes and adapting behavior. Error monitoring is associated with increased theta (4-7 Hz) EEG activity recorded at midfrontal electrode sites located over the medial frontal cortex. Increases in theta synchrony after errors between midfrontal and lateral electrode sites, located over lateral prefrontal, motor, and sensory/parietal brain regions, are associa...
Reliable confidence estimates are essential in semantic segmentation, especially in safety-critical settings where overconfident errors can mislead do...
Vision loss compromises the quality of life of millions of people worldwide. Currently, vision-restoring therapies are lacking. Post-mortem preservati...
To improve safety in Large Language Models (LLMs) we can either perform post-training alignment or exploit refusal directions in the activation space....
Background Large Language Models (LLMs) are increasingly explored for pharmacovigilance tasks, including information extraction, case documentation, a...
The accessible chemical space dwarfs any tractable screening budget, and most artificial intelligence drug discovery pipelines respond by docking and ...
Reinforcement learning (RL) post-training improves the reward alignment of flow-based generators, but often degrades perceptual quality in ways that a...
Current VLM evaluations often conflate language priors with genuine spatial reasoning. To address this, we introduce CRISP, a novel structural-diagnos...
Medical device recalls are a critical regulatory mechanism for protecting patient safety. The growing volume of FDA recall records presents challenges...
Short-form video platforms increasingly shape how young audiences encounter health information. Generative artificial intelligence can produce standar...
BackgroundInitiation of emergency dialysis, often requiring temporary catheter owing to unprepared definitive vascular access, is associated with infe...
Multimodal large language models (MLLMs) extend large language models (LLMs) with visual perception, enabling joint reasoning over images and text. De...
Quantitative maps from dynamic contrast-enhanced MRI (DCE-MRI) are essential for tumor assessment but are often unavailable due to contrast-agent risk...
General-purpose models often struggle to reliably identify and understand real-world multimodal risks, largely due to the inherent multimodal adversar...
Background: Manual review of 30-day hospital readmissions can identify actionable quality and safety problems, but it is labor-intensive. We developed...
Curvilinear object segmentation, including vessels and cracks, is challenging due to extreme spatial sparsity and topological fragility, where small l...
Road traffic accidents remain a critical global crisis, consistently serving as a primary driver of preventable mortality and severe injury. These inc...
The clinical and molecular heterogeneity observed in amyotrophic lateral sclerosis (ALS) presents a challenge for diagnosis, prognosis, and treatment....
Drug-induced liver injury (DILI) remains one of the most pressing challenges in drug development, contributing to 25-30% of late-stage clinical attrit...