Prevention of medical errors

Machine-Learning-Powered Neural Interfaces for Smart Prosthetics and Diagnostics

Advanced neural interfaces are transforming applications ranging from neuroscience research to diagnostic tools (for mental state recognition, tremor and seizure detection) as well as prosthetic devices (for motor and communication recovery). By integrating complex functions into miniaturized neural devices, these systems unlock significant opportunities for personalized assistive technologies a...

Task-Oriented Semantic Communication in Large Multimodal Models-based Vehicle Networks

Task-oriented semantic communication has emerged as a fundamental approach for enhancing performance in various communication scenarios. While recent advances in Generative Artificial Intelligence (GenAI), such as Large Language Models (LLMs), have been applied to semantic communication designs, the potential of Large Multimodal Models (LMMs) remains largely unexplored. In this paper, we investi...

Federated Causal Inference in Healthcare: Methods, Challenges, and Applications

Federated causal inference enables multi-site treatment effect estimation without sharing individual-level data, offering a privacy-preserving solut...

MaskClip: Detachable Clip-on Piezoelectric Sensing of Mask Surface Vibrations for Real-time Noise-Robust Speech Input

Masks are essential in medical settings and during infectious outbreaks but significantly impair speech communication, especially in environments wi...

NDDRF 2.0: An update and expansion of risk factor knowledge base for personalized prevention of neurodegenerative diseases.

INTRODUCTION: Neurodegenerative diseases (NDDs) are chronic diseases caused by brain neuron degeneration, requiring systematic integration of risk fac...

Short-Dipole Sensor Response Linearization Through Physics-Informed Neural Networks.

Short-dipole diode sensors loaded with highly resistive lines are commonly used to measure the time-averaged square of the high-frequency electromagne...

Integrating Artificial Intelligence in the Diagnosis and Management of Metabolic Syndrome: A Comprehensive Review.

BACKGROUND: Metabolic syndrome (MetS) is a progressive chronic pathophysiological state characterised by abdominal obesity, hypertension, hyperglycaem...

Latent Feature-Guided Conditional Diffusion for High-Fidelity Generative Image Semantic Communication

Semantic communication is proposed and expected to improve the efficiency and effectiveness of massive data transmission over sixth generation (6G) ...

Token-Level Prompt Mixture with Parameter-Free Routing for Federated Domain Generalization

Federated domain generalization (FedDG) aims to learn a globally generalizable model from decentralized clients with heterogeneous data while preser...

E-VLC: A Real-World Dataset for Event-based Visible Light Communication And Localization

Optical communication using modulated LEDs (e.g., visible light communication) is an emerging application for event cameras, thanks to their high sp...

Pseudo-Asynchronous Local SGD: Robust and Efficient Data-Parallel Training

Following AI scaling trends, frontier models continue to grow in size and continue to be trained on larger datasets. Training these models requires ...

Exhaled Breath Analysis Through the Lens of Molecular Communication: A Survey

Molecular Communication (MC) has long been envisioned to enable an Internet of Bio-Nano Things (IoBNT) with medical applications, where nanomachines...

Material Identification Via RFID For Smart Shopping

Cashierless stores rely on computer vision and RFID tags to associate shoppers with items, but concealed items placed in backpacks, pockets, or bags...

Deciphering the unique dynamic activation pathway in a G protein-coupled receptor enables unveiling biased signaling and identifying cryptic allosteric sites in conformational intermediates

Neurotensin receptor 1 (NTSR1), a member of the Class A G protein-coupled receptor superfamily, plays an important role in modulating dopaminergic n...

Can Knowledge Improve Security? A Coding-Enhanced Jamming Approach for Semantic Communication

As semantic communication (SemCom) attracts growing attention as a novel communication paradigm, ensuring the security of transmitted semantic infor...

Federated Learning of Low-Rank One-Shot Image Detection Models in Edge Devices with Scalable Accuracy and Compute Complexity

This paper introduces a novel federated learning framework termed LoRa-FL designed for training low-rank one-shot image detection models deployed on...

Blockchain Meets Adaptive Honeypots: A Trust-Aware Approach to Next-Gen IoT Security

Edge computing-based Next-Generation Wireless Networks (NGWN)-IoT offer enhanced bandwidth capacity for large-scale service provisioning but remain ...

Robust Planning and Control of Omnidirectional MRAVs for Aerial Communications in Wireless Networks

A new class of Multi-Rotor Aerial Vehicles (MRAVs), known as omnidirectional MRAVs (o-MRAVs), has gained attention for their ability to independentl...

FedC4: Graph Condensation Meets Client-Client Collaboration for Efficient and Private Federated Graph Learning

Federated Graph Learning (FGL) is an emerging distributed learning paradigm that enables collaborative model training over decentralized graph-struc...

LangCoop: Collaborative Driving with Language

Multi-agent collaboration holds great promise for enhancing the safety, reliability, and mobility of autonomous driving systems by enabling informat...