Prevention of medical errors

Is Discretization Fusion All You Need for Collaborative Perception?

Collaborative perception in multi-agent system enhances overall perceptual capabilities by facilitating the exchange of complementary information among agents. Current mainstream collaborative perception methods rely on discretized feature maps to conduct fusion, which however, lacks flexibility in extracting and transmitting the informative features and can hardly focus on the informative featu...

Non Line-of-Sight Optical Wireless Communication using Neuromorphic Cameras

Neuromorphic or event cameras, inspired by biological vision systems, capture changes in illumination with high temporal resolution and efficiency, producing streams of events rather than traditional images. In this paper, we explore the use of neuromorphic cameras for passive optical wireless communication (OWC), leveraging their asynchronous detection of illumination changes to decode data tra...

Towards Privacy-preserved Pre-training of Remote Sensing Foundation Models with Federated Mutual-guidance Learning

Traditional Remote Sensing Foundation models (RSFMs) are pre-trained with a data-centralized paradigm, through self-supervision on large-scale curat...

SIMAC: A Semantic-Driven Integrated Multimodal Sensing And Communication Framework

Traditional single-modality sensing faces limitations in accuracy and capability, and its decoupled implementation with communication systems increa...

Task-Oriented Co-Design of Communication, Computing, and Control for Edge-Enabled Industrial Cyber-Physical Systems

This paper proposes a task-oriented co-design framework that integrates communication, computing, and control to address the key challenges of bandw...

PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models

Despite recent advancements in federated learning (FL), the integration of generative models into FL has been limited due to challenges such as high...

Federated Multimodal Learning with Dual Adapters and Selective Pruning for Communication and Computational Efficiency

Federated Learning (FL) enables collaborative learning across distributed clients while preserving data privacy. However, FL faces significant chall...

Capture Global Feature Statistics for One-Shot Federated Learning

Traditional Federated Learning (FL) necessitates numerous rounds of communication between the server and clients, posing significant challenges incl...

Se-HiLo: Noise-Resilient Semantic Communication with High-and-Low Frequency Decomposition

Semantic communication has emerged as a transformative paradigm in next-generation communication systems, leveraging advanced artificial intelligenc...

Visual Embedding of Screen Sequences for User-Flow Search in Example-driven Communication

Effective communication of UX considerations to stakeholders (e.g., designers and developers) is a critical challenge for UX practitioners. To explo...

Psycholinguistic Analyses in Software Engineering Text: A Systematic Literature Review

Context: A deeper understanding of human factors in software engineering (SE) is essential for improving team collaboration, decision-making, and pr...

RiLoCo: An ISAC-oriented AI Solution to Build RIS-empowered Networks

The advance towards 6G networks comes with the promise of unprecedented performance in sensing and communication capabilities. The feat of achieving...

A semi-supervised learning approach to classify drug attributes in a pharmacy management database: A STROBE-compliant study.

With the development of information and communication technology, it has become possible to improve pharmacy management system (PMS) using these techn...

3HANDS Dataset: Learning from Humans for Generating Naturalistic Handovers with Supernumerary Robotic Limbs

Supernumerary robotic limbs (SRLs) are robotic structures integrated closely with the user's body, which augment human physical capabilities and nec...

Decentralized Personalization for Federated Medical Image Segmentation via Gossip Contrastive Mutual Learning

Federated Learning (FL) presents a promising avenue for collaborative model training among medical centers, facilitating knowledge exchange without ...

CoSDH: Communication-Efficient Collaborative Perception via Supply-Demand Awareness and Intermediate-Late Hybridization

Multi-agent collaborative perception enhances perceptual capabilities by utilizing information from multiple agents and is considered a fundamental ...

Designing VR Simulation System for Clinical Communication Training with LLMs-Based Embodied Conversational Agents

VR simulation in Health Professions (HP) education demonstrates huge potential, but fixed learning content with little customization limits its appl...

AI meets informed consent: a new era for clinical trial communication.

Clinical trials are fundamental to evidence-based medicine, providing patients with access to novel therapeutics and advancing scientific knowledge. H...

Factorized Deep Q-Network for Cooperative Multi-Agent Reinforcement Learning in Victim Tagging

Mass casualty incidents (MCIs) are a growing concern, characterized by complexity and uncertainty that demand adaptive decision-making strategies. T...

MedSimAI: Simulation and Formative Feedback Generation to Enhance Deliberate Practice in Medical Education

Medical education faces challenges in scalability, accessibility, and consistency, particularly in clinical skills training for physician-patient co...