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Prevention of medical errors

Latest AI and machine learning research in prevention of medical errors for healthcare professionals.

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ChronoMedicalWorld: A Medical World Model for Learning Patient Trajectories from Longitudinal Care Data

Long-horizon clinical simulation -- predicting how a patient's physiology evolves over years under s...

TouchMap-OR: Multi-View 3D Mapping of Hand-Surface Contacts

Hand-surface interactions between clinicians, patients, and medical equipment play a central role in...

CUOREMA: Immersive Bio & Behavioral Feedback and Digital Interventions for Cardiac Rehabilitation - Exploratory Analysis

Cardiac rehabilitation is critical for secondary prevention, yet long-term adherence remains low. We...

LPH-VTON: Resolving the Structure-Texture Dilemma of Virtual Try-On via Latent Process Handover

Virtual Try-On (VTON) aims to synthesize photorealistic images of garments precisely aligned with a ...

Emergent Communication between Heterogeneous Visual Agents through Decentralized Learning

Symbols are shared, but perception is private. We study emergent communication between heterogeneous...

On Privacy-Preserving Image Transmission in Low-Altitude Networks: A Swin Transformer-Based Framework with Federated Learning

The rapid development of low-altitude economy has driven the proliferation of Unmanned Aerial Vehicl...

FED-FSTQ: Fisher-Guided Token Quantization for Communication-Efficient Federated Fine-Tuning of LLMs on Edge Devices

Federated fine-tuning provides a practical route to adapt large language models (LLMs) on edge devic...

Where are they looking in the operating room?

Purpose: Gaze-following, the task of inferring where individuals are looking, has been widely studie...

Seeing Candidates at Scale: Multimodal LLMs for Visual Political Communication on Instagram

This paper presents a computational case study that evaluates the capabilities of specialized machin...

Statistics, Not Scale: Modular Medical Dialogue with Bayesian Belief Engine

Large language models are increasingly deployed as autonomous diagnostic agents, yet they conflate t...

PrivateBoost: Rethinking Federated Learning for Patient-Owned Medical Data: Learning from Single Records at Scale

The translation of artificial intelligence into clinical practice depends, in large part, on access ...

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

Reasoning post-training with reinforcement learning from verifiable rewards (RLVR) is typically stud...

Efficient Semantic Image Communication for Traffic Monitoring at the Edge

Many visual monitoring systems operate under strict communication constraints, where transmitting fu...

The Impact of Federated Learning on Distributed Remote Sensing Archives

Remote sensing archives are inherently distributed: Earth observation missions such as Sentinel-1, S...

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

Multi-agent coordination under partial observability requires agents to share complementary private ...

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

Robust 3D environmental perception is critical for applications such as autonomous driving and robot...

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

Deep learning based semantic communication has achieved significant progress in wireless image trans...

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