Explore support for Sustra / HF

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https://huggingface.co/spaces/owkin/substra

_Data scientists doing medical research often face a shortage of high quality and diverse data to effectively train models. This challenge can be overcome by securely allowing training on protected data through Federated Learning. Substra is a Python based Federated Learning software that enables researchers to easily train ML models on remote data regardless of the ML library they are using or the data type they are working with.

Here we show an example of image data located in two different hospitals.
By playing with the distribution of data in the two simulated hospitals, you’ll be able to compare how the federated models compare with models trained on single datasets. The data used is from the Camelyon17 dataset, a commonly used benchmark in the medical world that comes from this challenge. The sample below shows normal cells on the left compared with cancer cells on the right._