Learning under treatment-induced label indeterminacy with expert annotations of counterfactual outcomes in neurological prognostication
Read the original at arxiv.org→arXiv:2608.12477v1 Announce Type: new Abstract: Clinical prediction models are often developed as if the outcome of interest were cleanly observed for every patient. This assumption fails when treatment decisions...
Original headline: "Learning Under Treatment-Induced Label Indeterminacy with Expert Annotations of Counterfactual Outcomes: A Case Study in Neurological Prognostication"
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- Aug 14, 04:00 UTC arXiv cs.LG lead source Learning Under Treatment-Induced Label Indeterminacy with Expert Annotations of Counterfactual Outcomes: A Case Study in Neurological Prognostication