# Welcome!

{% hint style="warning" %}
This application represents the latest version of the federated learning module used in MEDomicsLab platform. We strive to keep both synchronized.
{% endhint %}

Welcome to the MEDfl-app documentation, where you will find all the resources you need to download, install and use the application.

### MEDomicsLab

This application is part of the [MEDomicsLab ](https://medomics-udes.gitbook.io/medomicslab-docs)project. It provides a graphical user interface to interact with the [MEDfl package](https://github.com/MEDomicsLab/MEDfl), enabling users to create federated learning experiments in both simulation and real world envirenement.

<figure><img src="/files/VC8OuFjkdiDP7LCZ1QW3" alt=""><figcaption></figcaption></figure>

### The MEDfl application

The MEDimage-app is a graphical implementation of the MEDfl Python package. It enables the use of all MEDfl functionalities through an interactive interface. These functionalities include creating, execute and analyse federated learning experiments in both simulation and real world senarios.

<figure><img src="/files/bpwPUkmt4mr0QvP6MIP5" alt=""><figcaption></figcaption></figure>

### Our goal

The goal of **MEDfl** is to provide a clear and progressive approach to federated learning that guides researchers from an initial idea to real-world deployment. MEDfl structures federated learning research into three stages: **conceptualization of the idea, simulation-based validation, and real-world experimentation**, enabling methodical and reproducible development.

A central objective of MEDfl is to **bridge the gap between computer science and medical research** by facilitating collaboration between these communities. By offering a shared experimental framework, MEDfl allows computer scientists and medical researchers to contribute their respective expertise while reducing technical and methodological barriers. Ultimately, MEDfl aims to simplify the federated learning process and support the effective translation of research ideas into practical medical applications.

<figure><img src="/files/hFFSpKplkZbwFYVbDFd0" alt=""><figcaption></figcaption></figure>

Before diving in, we recommend familiarizing yourself with the concepts of Federated learning. You can read more about radiomics [here](broken://pages/GHIivNlGHhS4Ze2OO12Y).

### Quick documentation guide

* To download and install the application, go to the [next page](/medfl-app-docs/quick-start.md).
* For tutorials, refer to the [radiomics page](broken://pages/GHIivNlGHhS4Ze2OO12Y).
* Use [*Forms* ](/medfl-app-docs/forms/contact-us.md)section to contact us or to report an issue.
* The [*Media* ](broken://pages/yVcsDP2xHOgCYPfqgh0T)section contains all our communication and interaction websites.
* If you are ready to add your touch to our application, refer to the [contribution page](/medfl-app-docs/contributing.md).


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://medomicslab.gitbook.io/medfl-app-docs/welcome.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
