SurvTRACE: Transformers for Survival Analysis with Competing Events. (arXiv:2110.00855v2 [cs.LG] UPDATED)

In medicine, survival analysis studies the time duration to events of
interest such as mortality. One major challenge is how to deal with multiple
competing events (e.g., multiple disease diagnoses). In this work, we propose a
transformer-based model that does not make the assumption for the underlying
survival distribution and is capable of handling competing events, namely
SurvTRACE. We account for the implicit \emph{confounders} in the observational
setting in multi-events scenarios, which causes selection bias as the predicted
survival probability …

analysis arxiv events lg survival transformers