Prevention of medical errors

DSFedMed: Dual-Scale Federated Medical Image Segmentation via Mutual Distillation Between Foundation and Lightweight Models

Foundation Models (FMs) have demonstrated strong generalization across diverse vision tasks. However, their deployment in federated settings is hindered by high computational demands, substantial communication overhead, and significant inference costs. We propose DSFedMed, a dual-scale federated framework that enables mutual knowledge distillation between a centralized foundation model and lightwe...

From Thought to Speech: Integrating a Low-Cost Electroencephalography Device with AI to Decode Neural Language Signals in Amyotrophic Lateral Sclerosis Patients

Purpose: Nearly all amyotrophic lateral sclerosis (ALS) patients develop dysarthria, with many progressing to anarthria and global expressive communication failure despite preserved consciousness. Despite the severity of this communication loss, available augmentative communication technologies remain limited. Brain-computer interface (BCI) technology provides a theoretically compelling approach f...

Communication-Efficient Federated Risk Difference Estimation for Time-to-Event Clinical Outcomes

Privacy-preserving model co-training in medical research is often hindered by server-dependent architectures incompatible with protected hospital data...

Predictive Modeling of Healthcare Workers' Priorities of WHO 2030 Key Activities for Snakebite Prevention and Control in Ghana

Snakebite is a neglected public health problem that results in significant morbidity and mortality, necessitating the World Health Organization (WHO) ...

MedMatch: a first step for the automation of large language model performance benchmarking for medication-related tasks

BackgroundThe accuracy and safety of generating medication orders by large language models (LLMs) must be demonstrated. Without standardization, perfo...

Topographic differences in EEG microstates: distinguishing juvenile myoclonic epilepsy from frontal lobe epilepsy.

UNLABELLED: This study aims to develop an exploratory classification model for Juvenile Myoclonic Epilepsy (JME) based on electroencephalogram (EEG) m...

Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection

Digital Twins (DT) have the potential to transform traffic management and operations by creating dynamic, virtual representations of transportation ...

Learning human-to-robot handovers through 3D scene reconstruction

Learning robot manipulation policies from raw, real-world image data requires a large number of robot-action trials in the physical environment. Alt...

AdeptHEQ-FL: Adaptive Homomorphic Encryption for Federated Learning of Hybrid Classical-Quantum Models with Dynamic Layer Sparing

Federated Learning (FL) faces inherent challenges in balancing model performance, privacy preservation, and communication efficiency, especially in ...

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models

Federated Learning (FL), as a distributed learning paradigm, trains models over distributed clients' data. FL is particularly beneficial for distrib...

Prototype-Guided and Lightweight Adapters for Inherent Interpretation and Generalisation in Federated Learning

Federated learning (FL) provides a promising paradigm for collaboratively training machine learning models across distributed data sources while mai...

Cooperative Mapping, Localization, and Beam Management via Multi-Modal SLAM in ISAC Systems

Simultaneous localization and mapping (SLAM) plays a critical role in integrated sensing and communication (ISAC) systems for sixth-generation (6G) ...

[The standardization and digitalization and intelligentization represent the future development direction of hip arthroscopy diagnosis and treatment technology].

In recent years, hip arthroscopy has made great progress and has been extended to the treatment of intra-articular or periarticular diseases. However,...

Multimodal LLM Integrated Semantic Communications for 6G Immersive Experiences

6G networks promise revolutionary immersive communication experiences including augmented reality (AR), virtual reality (VR), and holographic commun...

Characterizing Compute-Communication Overlap in GPU-Accelerated Distributed Deep Learning: Performance and Power Implications

This paper provides an in-depth characterization of GPU-accelerated systems, to understand the interplay between overlapping computation and communi...

A Late Collaborative Perception Framework for 3D Multi-Object and Multi-Source Association and Fusion

In autonomous driving, recent research has increasingly focused on collaborative perception based on deep learning to overcome the limitations of in...

PAL: Designing Conversational Agents as Scalable, Cooperative Patient Simulators for Palliative-Care Training

Effective communication in serious illness and palliative care is essential but often under-taught due to limited access to training resources like ...

Reconfigurable Intelligent Surface aided Integrated-Navigation-and-Communication in Urban Canyons: A Satellite Selection Approach

This study investigates the application of a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided medium-Ear...

Multi-User Generative Semantic Communication with Intent-Aware Semantic-Splitting Multiple Access

With the booming development of generative artificial intelligence (GAI), semantic communication (SemCom) has emerged as a new paradigm for reliable...

AI Meets Maritime Training: Precision Analytics for Enhanced Safety and Performance

Traditional simulator-based training for maritime professionals is critical for ensuring safety at sea but often depends on subjective trainer asses...