Latest AI and machine learning research in clinical trials for healthcare professionals.
BACKGROUND: Effective communication skills are fundamental for health care professionals, yet conventional training methods face challenges in scalability and accessibility due to resource constraints. The emergence of artificial intelligence (AI), particularly generative AI, offers innovative ways for enhancing communication skills training by simulating realistic conversational scenarios and pro...
INTRODUCTION: Intensive care unit-acquired weakness (ICUAW) is a common and severe complication in critically ill patients, associated with high morbidity and poor prognosis. Despite increasing focus on ICUAW, definitive diagnostic and therapeutic strategies remain absent. Early mobilisation has been demonstrated as an effective intervention for preventing and alleviating ICUAW. This study aims to...
We are surrounded by robots helping us perform complex tasks. Robots have a wide range of applications, from industrial automation to personalized a...
The acquisition of agentic capabilities has transformed LLMs from "knowledge providers" to "action executors", a trend that while expanding LLMs' ca...
To investigate the prediction of a model constructed by combining machine learning (ML) with clinical features and ultrasound radiomics in the clinica...
This study examines the impact of an AI instructional agent on students' perceived learner control and academic performance in a medium demanding co...
Recent advancements in world models have revolutionized dynamic environment simulation, allowing systems to foresee future states and assess potenti...
Recent advancements in world models have revolutionized dynamic environment simulation, allowing systems to foresee future states and assess potenti...
While (multimodal) large language models (LLMs) have attracted widespread attention due to their exceptional capabilities, they remain vulnerable to...
Do LLMs robustly generalize critical safety facts to novel situations? Lacking this ability is dangerous when users ask naive questions. For instanc...
Traffic safety science has long been hindered by a fundamental data paradox: the crashes we most wish to prevent are precisely those events we rarel...
Large language models (LLMs) exhibit advancing capabilities in complex tasks, such as reasoning and graduate-level question answering, yet their res...
Text-to-Image (T2I) models have achieved remarkable success in generating visual content from text inputs. Although multiple safety alignment strate...
BACKGROUND: Clinical operative skills training is a critical component of preclinical education for dental students. Although technology-assisted inst...
Optimization-based jailbreaks typically adopt the Toxic-Continuation setting in large vision-language models (LVLMs), following the standard next-to...
The rapid advancement of vision-language models (VLMs) has brought a lot of attention to their safety alignment. However, existing methods have prim...
Vision-Language Models (VLMs) exhibit impressive performance, yet the integration of powerful vision encoders has significantly broadened their atta...
Traffic signal control (TSC) is a core challenge in urban mobility, where real-time decisions must balance efficiency and safety. Existing methods -...
The emergence of large language models (LLMs) enables the development of intelligent agents capable of engaging in complex and multi-turn dialogues....
Text-to-image (T2I) generation models can inadvertently produce not-safe-for-work (NSFW) content, prompting the integration of text and image safety...