# Adversarial Time-to-Event Modeling

@article{Chapfuwa2018AdversarialTM, title={Adversarial Time-to-Event Modeling}, author={Paidamoyo Chapfuwa and Chenyang Tao and Chunyuan Li and Courtney Page and Benjamin Goldstein and Lawrence Carin and Ricardo Henao}, journal={Proceedings of machine learning research}, year={2018}, volume={80}, pages={ 735-744 } }

Modern health data science applications leverage abundant molecular and electronic health data, providing opportunities for machine learning to build statistical models to support clinical practice. [...] Key Method We also introduce a principled cost function to exploit information from censored events (events that occur subsequent to the observation window). Unlike most time-to-event models, we focus on the estimation of time-to-event distributions, rather than time ordering. We validate our model on both… Expand

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