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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 <!--- Put an `x` in all the boxes that apply, and remove the not applicable items --> - [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 <path to .ipynb file>` --------- Signed-off-by: Zilinghan <zl52@illinois.edu>
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federated_learning/appfl/README.md

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# Federated learning with APPFL
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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).

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