arXiv:2602. 22179v2 Announce Type: replace Abstract: In many applications, it is important to identify subpopulations that survive longer or shorter than the rest of the population.
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arXiv:2512.16481v2 Announce Type: replace-cross Abstract: Survival analysis encompasses a broad range of methods for analyzing time-to-event data, with one key objective being the comparison of survi...
arXiv:2504. 20908v3 Announce Type: replace Abstract: Current subgroup identification methods typically follow a two-step approach: first estimate conditional average treatment effects and then apply thresholding or rule-based procedures to define subgroups.
arXiv:2608. 00271v1 Announce Type: cross Abstract: A wide range of statistical and machine learning methods have been proposed for survival analysis with competing risks, where the occurrence of one event (i.
arXiv:2606. 14608v1 Announce Type: cross Abstract: Survival prediction plays a central role for healthcare providers and clinical researchers.
arXiv:2609.38181v1 Announce Type: new Abstract: Survival analysis estimates time-to-event outcomes from patient covariates and is widely used for medical risk assessment. Patients seeking prognostic...
arXiv:2606. 02671v1 Announce Type: cross Abstract: Machine learning predictors have become essential tools for guiding automated decision making.