This is the documentation for the FeTS Platform, developed by CBICA at UPenn, in collaboration with Intel Labs, Intel AI and Intel IOT
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To enable distributed testing and training machine learning models without direct access to collaborator data, FeTS uses a technique called Federated Learning. The Open Federated Learning (OpenFL) framework is developed as part of a collaboration between Intel and the University of Pennsylvania (UPenn), as a part of Intel’s commitment in supporting the grant awarded to the Center for Biomedical Image Computing and Analytics at UPenn (PI: S.Bakas) from the Informatics Technology for Cancer Research (ITCR) program of the National Cancer Institute (NCI) of the National Institutes of Health (NIH), for the development of the Federated Tumor Segmentation (FeTS, www.fets.ai) platform (grant award number: U01-CA242871).
For more details, please visit us at https://www.fets.ai/
For issues, please visit https://github.com/FETS-AI/Front-End/issues