Latest AI and machine learning research in clinical trials for healthcare professionals.
Clinical research advances slowly because its core tasks, from evidence synthesis to mechanistic validation, remain fragmented. We present MedGenesis, a clinical artificial intelligence (AI) scientist built on a world-model reasoning loop that jointly updates a Latent Hypothesis Space and a Latent Action Space under expected information gain (EIG), uncertainty reduction (UR), and a safety prior P(...
Conventional vision-language models are largely object-centric, focusing on detecting and describing individual entities. In safety-critical X-ray baggage screening, however, threat often emerges not from a single object but from the functional compatibility of spatially dispersed components, such as batteries, detonators, and explosive charges. We formalize this setting as \emph{compositional thr...
General-purpose models often struggle to reliably identify and understand real-world multimodal risks, largely due to the inherent multimodal adversar...
Speculative decoding accelerates inference by letting a draft model propose tokens for a target model to verify, raising a concrete safety question: a...
Background: Efficient cerebral microhemorrhage (MCH) monitoring is critical for anti-amyloid therapy safety due to ARIA-H risk. We developed MCH-Guard...
Vision-language models (VLMs) are increasingly deployed in consumer, medical, financial, and enterprise applications. This broad deployment expands th...
Flow matching has recently emerged as a strong paradigm for state-of-the-art text-to-image (T2I) generation, enabling high-quality generation with a s...
Robotic ultrasound scanning in real clinical environments requires both high-level clinical workflow reasoning and low-level closed-loop execution. Ph...
Background: Children and young people (CYP) are particularly affected by mental health problems. Mobile apps provide a scalable and accessible approac...
Neural network controllers for autonomous decision-making are well-established in cyber-physical systems, yet their deployment in safety-critical heal...
Nickel has been studied for a long time as an environmental contaminant but less so in its connection to population health. It does not announce itsel...
Open-weight video diffusion models can generate photorealistic unsafe content, from violence to misinformation, yet existing defenses either require e...
Large Language Models (LLMs) are increasingly deployed in healthcare settings, yet their tendency to hallucinate poses risks when clinical decisions a...
Background and rationale: Knee osteoarthritis (KOA) is a leading cause of lower limb disability worldwide, characterized by functional limitations, st...
Autonomous network-security response systems promise to reduce Security Operations Centre (SOC) reaction latency, but reward-only multi-agent reinforc...
In primary care and outpatient settings, clinically important patient information is often embedded in fragmented, ambiguous, repetitive, and noisy co...
Introduction: Precise anatomical navigation is fundamental to safe endoscopic pituitary surgery, a high-stakes procedure characterised by a challengin...
Post-traumatic stress disorder (PTSD) in veterans is characterized by persistent hyperarousal and comorbid anxiety and depressive symptoms that are di...
Personalized medicine in acute ischemic stroke requires moving beyond average treatment effects (ATE) to individualized treatment effect (ITE) estimat...
Objective. To introduce PsiBench, a clinically validated medication-safety benchmark for evaluating large language models (LLMs) against the standards...