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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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FedPaI: Achieving Extreme Sparsity in Federated Learning via Pruning at Initialization

Federated Learning (FL) enables distributed training on edge devices but faces significant challen...

(1)
Machine learning in cardiovascular risk assessment: Towards a precision medicine approach.

Cardiovascular diseases remain the leading cause of global morbidity and mortality. Validated risk s...

Apr 2025 40191920
Artificial intelligence in colorectal surgery multidisciplinary team approach-From innovation to application.

Artificial intelligence (AI) has played a novel role in aiding healthcare system functions and enhan...

Apr 2025 40285450
An Integrated AI-Enabled System Using One Class Twin Cross Learning (OCT-X) for Early Gastric Cancer Detection

Early detection of gastric cancer, a leading cause of cancer-related mortality worldwide, remains ...

Communication-Efficient and Personalized Federated Foundation Model Fine-Tuning via Tri-Matrix Adaptation

In federated learning, fine-tuning pre-trained foundation models poses significant challenges, par...

Towards Secure Semantic Communications in the Presence of Intelligent Eavesdroppers

Semantic communication has emerged as a promising paradigm for enhancing communication efficiency ...

(1)
Route-and-Aggregate Decentralized Federated Learning Under Communication Errors

Decentralized federated learning (D-FL) allows clients to aggregate learning models locally, offer...

Utsarjan: A smartphone App for providing kidney care and real-time assistance to children with nephrotic syndrome

Background Telemedicine has the potential to provide secure and cost-effective healthcare at the t...

(3)
Exploring Textual Semantics Diversity for Image Transmission in Semantic Communication Systems using Visual Language Model

In recent years, the rapid development of machine learning has brought reforms and challenges to t...

Rethinking Glaucoma Calibration: Voting-Based Binocular and Metadata Integration

Glaucoma is an incurable ophthalmic disease that damages the optic nerve, leads to vision loss, an...

Which2comm: An Efficient Collaborative Perception Framework for 3D Object Detection

Collaborative perception allows real-time inter-agent information exchange and thus offers invalua...

Mapping intellectual structure and research hotspots of cancer studies in primary health care: A machine-learning-based analysis.

In the contemporary fight against cancer, primary health care (PHC) services hold a significant and ...

(3)
Mar 2025 40128045
Federated Continual 3D Segmentation With Single-round Communication

Federated learning seeks to foster collaboration among distributed clients while preserving the pr...

FedSCA: Federated Tuning with Similarity-guided Collaborative Aggregation for Heterogeneous Medical Image Segmentation

Transformer-based foundation models (FMs) have recently demonstrated remarkable performance in med...

UltraFlwr -- An Efficient Federated Medical and Surgical Object Detection Framework

Object detection shows promise for medical and surgical applications such as cell counting and too...

Is Discretization Fusion All You Need for Collaborative Perception?

Collaborative perception in multi-agent system enhances overall perceptual capabilities by facilit...

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

Neuromorphic or event cameras, inspired by biological vision systems, capture changes in illuminat...

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 parad...

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