Bayesian federated inference for estimating statistical models based on non‐shared multicenter data sets
Marianne A Jonker,
Hassan Pazira,
Anthony CC Coolen
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 been merged. It seeks to har… Show more
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