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Tabular foundation models are not a shortcut to calibrated clinical risk prediction: a pre-registered simulation against the true risk
Tabular foundation models are pretrained networks that predict risk from a table without fitting a model. Whether their risks are correct (calibrated) has been judged on real data, where true risk is unknown. In a pre-registered simulation with known true risks, we compared TabPFN-3.5, TabICLv2 and
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