From f1de38f464ae19d960dde5d546bf42398cde7856 Mon Sep 17 00:00:00 2001 From: Zilinghan Li <67045903+Zilinghan@users.noreply.github.com> Date: Thu, 6 Feb 2025 09:30:01 -0600 Subject: [PATCH] Add documentation for APPFL+MONAI integration to do federated learning (#1941) ### Description In this pull request, I added documentation for the APPFL+MONAI integration to do federated learning. ### Checks - [x] Avoid including large-size files in the PR. - [x] Clean up long text outputs from code cells in the notebook. - [x] For security purposes, please check the contents and remove any sensitive info such as user names and private key. - [x] Ensure (1) hyperlinks and markdown anchors are working (2) use relative paths for tutorial repo files (3) put figure and graphs in the `./figure` folder - [ ] Notebook runs automatically `./runner.sh -t ` --------- Signed-off-by: Zilinghan --- federated_learning/appfl/README.md | 3 +++ 1 file changed, 3 insertions(+) create mode 100644 federated_learning/appfl/README.md diff --git a/federated_learning/appfl/README.md b/federated_learning/appfl/README.md new file mode 100644 index 000000000..e2ab6d85f --- /dev/null +++ b/federated_learning/appfl/README.md @@ -0,0 +1,3 @@ +# Federated learning with APPFL + +The Advanced Privacy Preserving Federated Learning framework, [APPFL](https://github.com/APPFL/APPFL), provides an example on how to use its `MonaiTrainer` to train federated learning models using MONAI's [FL components](https://docs.monai.io/en/latest/fl.html). The tutorial is available at [here](https://appfl.ai/en/latest/tutorials/examples_monai.html).