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stat.ML2025
Discovery and inference beyond linearity for epidemiological data by integrating Bayesian regression, tree ensembles and Shapley values
Giorgio Spadaccini, Marjolein Fokkema, Mark A. van de Wiel
Machine Learning (ML) is gaining popularity in epidemiology and healthcare studies for hypothesis-free discovery of risk and protective factors. ML is strong at discovering nonline…
stat.ML2023
Co-data Learning for Bayesian Additive Regression Trees
Jeroen M. Goedhart, Thomas Klausch, Jurriaan Janssen +1
Medical prediction applications often need to deal with small sample sizes compared to the number of covariates. Such data pose problems for prediction and variable selection, espe…