MEDomicsLab-docs
V0
V0
  • 👋Welcome!
  • 👊Quick start
  • 👀Overview
  • 🧑‍🏫Tutorials
    • 🔵Design
      • Extraction Module
        • Image Extraction Page
        • Text Extraction Page
        • Time Series Extraction Page
        • MEDimage
      • Input Module
        • Feature Reduction Tool
        • MEDprofiles
          • MEDprofiles Viewer
      • Exploratory Module
    • 🟠Development
      • Learning Module
      • Evaluation Module
      • Federated Learning Module
        • Overview
        • Configure database
        • Create pipelines
        • Pipeline results
        • Hyperparameters optimization
        • Merge results
        • Crash tutorial
    • 🟢Deployment
      • Application Module
    • 🛠️Miscellaneous
  • 📄Testing Phase with MIMIC
    • MIMIC data access
    • Step 1: Install and Explore
    • Step 2: Extract Data
    • Step 3: Prepare ML tables
    • Step 4: Explore Data
    • Step 5: Vacations
    • Step 6: Create Model
    • Step 7: Evaluate & Apply Model
    • Step 8: Challenge
    • Wrap-Up
  • 👩‍💻Contributing
    • Our coding standards
    • How to push my modification ?
  • 🤕Troubleshooting
  • ❓FAQ
  • 🤓About us
  • Important Links
    • Official Website
    • 📔Release Notes
    • 🥲Known Issues
    • 😎Project Board
    • 🧬Physionet
  • MEDIA
    • ⚛️MEDomics
    • 👾Discord
    • 😺Github
    • 📺YouTube
  • Forms
    • 🗣️Contact us
    • 📝Report an issue
    • ‼️Join the testing phase
Powered by GitBook
On this page
  1. Tutorials
  2. Development

Federated Learning Module

PreviousEvaluation ModuleNextOverview

The Federated Learning module in MEDomicsLab is the third component of the development layer, responsible for conducting federated learning training. Federated learning allows multiple parties to collaboratively train a shared machine learning model without sharing their raw data. This module facilitates decentralized model training across distributed datasets while preserving data privacy and security. It enables researchers and developers to build, optimize, and deploy federated learning models efficiently within the MEDomicsLab platform.

For more information on federated learning, you can read more and explore from Google AI Blog.

LET'S GET STARTED!

🧑‍🏫
🟠
here
this article