BIOENGINEER

Carbon-Budgeted Federated Learning Adds Blockchain Auditing to Healthcare AI

A simulated federated learning framework combines carbon-budgeted client selection, blockchain auditing, and ...
BIOENGINEER

Federated, explainable AI framework classifies Alzheimer’s disease from MRI and clinical data

A federated learning framework combining MRI and clinical data classifies Alzheimer's disease with reported accuracy up to 94 ...
Mirage News

Federated Learning Enables Joint AI Development Across Institutions

Medical imaging supports the planning of modern radiation therapy, with federated AI approaches possibly opening up new ...
Devdiscourse

AI Framework Boosts 6G Traffic Forecasts and Threat Detection in Benchmark Tests

FALCON-6G combines federated learning and language models to improve network traffic prediction and intrusion detection. Benchmark tests showed better accuracy, faster decisions and lower ...

Researchers develop privacy-friendly, secure and sustainable AI techniques for medical imaging

Artificial intelligence can be helpful in analyzing medical images and support radiotherapy planning workflows. However, huge ...
EurekAlert!

DFUN-KDF: A knowledge distillation-based decentralized federated learning framework for uav network optimization

As the use of Unmanned Aerial Vehicles (UAVs) expands across various fields, there is growing interest in leveraging Federated Learning (FL) to enhance the efficiency of UAV networks. However, ...
techtarget

Federated Learning Framework Aims to Improve Fairness in AI Screening Tools

A research team from the University of Pittsburgh (Pitt) Swanson School of Engineering has been awarded a $1.7 million National Institutes of Health grant to develop a federated learning (FL)-based ...
EurekAlert!

Federated learning-outcome prediction with multi-layer privacy protection

The FecMap model trained in an iterative manner. An FL communication is completed by (1) training the local model, (2) uploading to the server, (3) computing the global model, and (4) updating the ...
Forbes

IBM Federated Learning Research - Extracting Machine Learning Models From Multiple Data Pools

As machine learning becomes more pervasive in the data center and the cloud there will be a need to share and aggregate information and knowledge but without exposing or moving the underlying data.