Prevention of medical errors

PubSwap: Public-Data Off-Policy Coordination for Federated RLVR

Reasoning post-training with reinforcement learning from verifiable rewards (RLVR) is typically studied in centralized settings, yet many realistic applications involve decentralized private data distributed across organizations. Federated training is a natural solution, but scaling RLVR in this regime is challenging: full-model synchronization is expensive, and performing many local steps can cau...

Efficient Semantic Image Communication for Traffic Monitoring at the Edge

Many visual monitoring systems operate under strict communication constraints, where transmitting full-resolution images is impractical and often unnecessary. In such settings, visual data is often used for object presence, spatial relationships, and scene context rather than exact pixel fidelity. This paper presents two semantic image communication pipelines for traffic monitoring, MMSD and SAMR,...

No One Left Behind: Adaptive Tablet Modalities for Digitally Excluded Emergency Department Patients Design, Implementation, and Social Evidence for an Impairment-First Interface

Background: The urgent care departments in Europe face a structural paradox: accelerating digitalisation is accompanied by a patient population that i...

The Impact of Federated Learning on Distributed Remote Sensing Archives

Remote sensing archives are inherently distributed: Earth observation missions such as Sentinel-1, Sentinel-2, and Sentinel-3 have collectively accumu...

Multi-Agent Decision-Focused Learning via Value-Aware Sequential Communication

Multi-agent coordination under partial observability requires agents to share complementary private information. While recent methods optimize message...

Rascene: High-Fidelity 3D Scene Imaging with mmWave Communication Signals

Robust 3D environmental perception is critical for applications such as autonomous driving and robot navigation. However, optical sensors such as came...

Adaptive Semantic Communication for Wireless Image Transmission Leveraging Mixture-of-Experts Mechanism

Deep learning based semantic communication has achieved significant progress in wireless image transmission, but most existing schemes rely on fixed m...

QuantumXCT: Learning Interaction-Induced State Transformation in Cell-Cell Communication via Quantum Entanglement and Generative Modeling

Inferring cell-cell communication (CCC) from single-cell transcriptomics remains fundamentally limited by reliance on curated ligand-receptor database...

Gaussian Shannon: High-Precision Diffusion Model Watermarking Based on Communication

Diffusion models generate high-quality images but pose serious risks like copyright violation and disinformation. Watermarking is a key defense for tr...

PRIME-CVD: A Parametrically Rendered Informatics Medical Environment for Education in Cardiovascular Risk Modelling

In recent years, progress in medical informatics and machine learning has been accelerated by the availability of openly accessible benchmark datasets...

Mapping spatial cell-cell communication programs by tailoring chains of cells for transformer neural networks

Recent advances in spatial transcriptomics and computational modeling enable the study of cellular interactions in situ. However, existing methods qua...

A Scoping Review of AI-Driven Digital Interventions in Mental Health Care: Mapping Applications Across Screening, Support, Monitoring, Prevention, and Clinical Education

Artificial intelligence (AI)-enabled digital interventions, including Generative AI (GenAI) and Human-Centered AI (HCAI), are increasingly used to exp...

IConE: Batch Independent Collapse Prevention for Self-Supervised Representation Learning

Self-supervised learning (SSL) has revolutionized representation learning, with Joint-Embedding Architectures (JEAs) emerging as an effective approach...

FL-MedSegBench: A Comprehensive Benchmark for Federated Learning on Medical Image Segmentation

Federated learning (FL) offers a privacy-preserving paradigm for collaborative medical image analysis without sharing raw data. However, the absence o...

UAV-MARL: Multi-Agent Reinforcement Learning for Time-Critical and Dynamic Medical Supply Delivery

Unmanned aerial vehicles (UAVs) are increasingly used to support time-critical medical supply delivery, providing rapid and flexible logistics during ...

Med-DualLoRA: Local Adaptation of Foundation Models for 3D Cardiac MRI

Foundation models (FMs) show great promise for robust downstream performance across medical imaging tasks and modalities, including cardiac magnetic r...

Shifting Adaptation from Weight Space to Memory Space: A Memory-Augmented Agent for Medical Image Segmentation

Medical image segmentation is fundamental to clinical workflows, yet models trained on a single dataset often fail to generalize across institutions, ...

AI-Generated Responses to Patient's Messages: Effectiveness, Feasibility and Implementation

Background Generative artificial intelligence (GenAI) in healthcare may reduce administrative burden and enhance quality of care. Large language model...

Leveraging large language models to address common vaccination myths and misconceptions

Large language models (LLMs) are increasingly used by the public to seek health information, yet their reliability in addressing common vaccine myths ...

Doubly Adaptive Channel and Spatial Attention for Semantic Image Communication by IoT Devices

Internet of Things (IoT) networks face significant challenges such as limited communication bandwidth, constrained computational and energy resources,...