Federated learning system for medical image classification using Flower and PyTorch. Trains a CNN on MNIST across clients, with differential privacy via Opacus. Visualizes accuracy/loss with Chart.js.

Federated learning (FL) allows hospitals and medical centers to train models without sharing patient data. Instead of sending data to a central server, each institution trains the model locally and ...

Background Diagnosing the presence of metastasis of pancreatic cancer is pivotal for patient management and treatment, with ...

Patient classification systems can have negative consequences, especially under scarcity by University of Deusto edited by Gaby Clark , reviewed by Robert Egan ...

Federated learning empowers the privacy-preserving training of a global model in decentralized medical scenarios. Subsequently, personalized and clustered federated learning have been respectively ...

This project compares Centralized Machine Learning (CML) and Federated Learning (FL) for animal image classification using a filtered subset of the CIFAR-10 dataset (cats, dogs, frogs).

While reviewing AI image generators, I've created some truly terrible content. Take a good laugh, then learn how to fix these annoyingly common problems. How to Fix the Most Common AI Image Errors ...

AMC Networks is the latest entertainment entity — and the first cable player — to formally make a deal with emerging Hollywood AI player Runway, THR has learned. AMC will use the New York firm ...

A new six-part podcast explores the story of medical treatment for transgender young people — how the care began, the lives it changed, and the legal and political fights that could end it in ...

Cave Spring High School 9th grader Katie Sempek is diving into the world of healthcare this summer. Instead of spending Friday at the pool or out with her friends, she was learning how to run an ...