Public Health & Policy

Clinical Trials

Latest AI and machine learning research in clinical trials for healthcare professionals.

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When Understanding Becomes a Risk: Authenticity and Safety Risks in the Emerging Image Generation Paradigm

Recently, multimodal large language models (MLLMs) have emerged as a unified paradigm for language a...

Multi-Agent Reasoning with Consistency Verification Improves Uncertainty Calibration in Medical MCQA

Miscalibrated confidence scores are a practical obstacle to deploying AI in clinical settings. A mod...

A deep-learning based biomarker of systemic cellular senescence burden to predict mortality and health outcomes

Introduction: The accumulation of senescent cells is a recognized hallmark of biological aging and i...

ENC-Bench: A Benchmark for Evaluating Multimodal Large Language Models in Electronic Navigational Chart Understanding

Electronic Navigational Charts (ENCs) are the safety-critical backbone of modern maritime navigation...

SynForceNet: A Force-Driven Global-Local Latent Representation Framework for Lithium-Ion Battery Fault Diagnosis

Online safety fault diagnosis is essential for lithium-ion batteries in electric vehicles(EVs), part...

JANUS: A Lightweight Framework for Jailbreaking Text-to-Image Models via Distribution Optimization

Text-to-image (T2I) models such as Stable Diffusion and DALLE remain susceptible to generating harmf...

ARYA: A Physics-Constrained Composable & Deterministic World Model Architecture

This paper presents ARYA, a composable, physics-constrained, deterministic world model architecture ...

The Effects of AI-Guided Exercise and a Smart Ring on Arterial Stiffness (GONDOR-AS): protocol for a randomized controlled trial

Background: Cardiovascular disease (CVD) prevention is limited by the major challenge of low long-te...

From Concept to Clinic: Real World Evidence for Autonomous AI Deployment in Primary Care Telemedicine

Systems powered by large language models are widely used for health information and advice, yet robu...

Aggregate benchmark scores obscure patient safety implications of errors across frontier language models

Frontier language models are widely used for health-related queries, yet aggregate benchmark scores ...

Clinician Experiences with Ambient AI Scribe Technology in Singapore: A Qualitative Study

Background: The administrative burden of clinical documentation is a recognised contributor to clini...

MicroVision: An Open Dataset and Benchmark Models for Detecting Vulnerable Road Users and Micromobility Vehicles

Micromobility is a growing mode of transportation, raising new challenges for traffic safety and pla...

OpenScientist: evaluating an open agentic AI co-scientist to accelerate biomedical discovery

Background: Advances in medicine depend on analyzing large and complex data sources, but discovery i...

UniSAFE: A Comprehensive Benchmark for Safety Evaluation of Unified Multimodal Models

Unified Multimodal Models (UMMs) offer powerful cross-modality capabilities but introduce new safety...

Generalist Multimodal LLMs Gain Biometric Expertise via Human Salience

Iris presentation attack detection (PAD) is critical for secure biometric deployments, yet developin...

SynAPSeg: A novel dataset and image analysis framework for deep learning-based synapse detection and quantification

Synapses are the fundamental units of neural computation, yet quantifying their organization across ...

Evolving Contextual Safety in Multi-Modal Large Language Models via Inference-Time Self-Reflective Memory

Multi-modal Large Language Models (MLLMs) have achieved remarkable performance across a wide range o...

Detection of Autonomous Shuttles in Urban Traffic Images Using Adaptive Residual Context

The progressive automation of transport promises to enhance safety and sustainability through shared...

Artificial Intelligence in Mammography Screening in Norway (AIMS Norway): Protocol for a randomized controlled trial

Background and Objective: Increasing screening volumes, combined with global shortage of radiologist...

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