VectorInstitute/FL4Health
A flexible, modular, and easy to use library to facilitate federated learning research and development in healthcare settings
This tool helps healthcare organizations collaboratively train machine learning models using sensitive patient data, without directly sharing the raw data. It takes secure, decentralized healthcare datasets and produces a robust, privacy-preserving AI model. Medical researchers, hospital data scientists, and healthcare AI developers can use this to build more accurate models across various institutions.
Use this if you need to develop AI models in healthcare by combining insights from multiple patient datasets, while strictly adhering to privacy regulations and data governance policies.
Not ideal if your data can be freely shared and centralized without privacy concerns, or if you need to analyze individual patient records directly across different institutions.
Stars
52
Forks
16
Language
Python
License
—
Category
Last pushed
Mar 12, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/VectorInstitute/FL4Health"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
flwrlabs/flower
Flower: A Friendly Federated AI Framework
JonasGeiping/breaching
Breaching privacy in federated learning scenarios for vision and text
zama-ai/concrete-ml
Concrete ML: Privacy Preserving ML framework using Fully Homomorphic Encryption (FHE), built on...
anupamkliv/FedERA
FedERA is a modular and fully customizable open-source FL framework, aiming to address these...
p2pfl/p2pfl
P2PFL is a decentralized federated learning library that enables federated learning on...