Bayesian Federated Inference for estimating Statistical Models based on Non-shared Multicenter Data sets

arXiv:2302.07677v2 Announce Type: replace-cross
Abstract: Identifying predictive factors for an outcome of interest via a multivariable analysis is often difficult when the data set is small. Combining data from different medical centers into a single (larger) database would alleviate this problem, but is in practice challenging due to regulatory and logistic problems. Federated Learning (FL) is a machine learning approach that aims to construct from local inferences in separate data centers what would have been inferred had the data sets …

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