Federated Survival Analysis with Discrete-Time Cox Models

16 Jun 2020Mathieu AndreuxAndre ManoelRomuald MenuetCharlie SaillardChloé Simpson

Building machine learning models from decentralized datasets located in different centers with federated learning (FL) is a promising approach to circumvent local data scarcity while preserving privacy. However, the prominent Cox proportional hazards (PH) model, used for survival analysis, does not fit the FL framework, as its loss function is non-separable with respect to the samples... (read more)

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