Counterfactual Phenotyping with Censored Time-to-Events. (arXiv:2202.11089v3 [cs.LG] UPDATED)

Estimation of treatment efficacy of real-world clinical interventions
involves working with continuous outcomes such as time-to-death,
re-hospitalization, or a composite event that may be subject to censoring.
Counterfactual reasoning in such scenarios requires decoupling the effects of
confounding physiological characteristics that affect baseline survival rates
from the effects of the interventions being assessed. In this paper, we present
a latent variable approach to model heterogeneous treatment effects by
proposing that an individual can belong to one of latent clusters with …

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