4 citations · 4 across the 1 of their papers we have counts for
3 papers
A framework for leveraging machine learning tools to estimate personalized survival curves
Charles J. Wolock, Peter B. Gilbert, Noah Simon +1
The conditional survival function of a time-to-event outcome subject to censoring and truncation is a common target of estimation in survival analysis. This parameter may be of sci…
Investigating symptom duration using current status data: a case study of post-acute COVID-19 syndrome
Charles J. Wolock, Susan Jacob, Julia C. Bennett +9
For infectious diseases, characterizing symptom duration is of clinical and public health importance. Symptom duration may be assessed by surveying infected individuals and queryin…
Debiased machine learning for counterfactual survival functionals based on left-truncated right-censored data
Eric R. Morenz, Charles J. Wolock, Marco Carone
Learning causal effects of a binary exposure on time-to-event endpoints can be challenging because survival times may be partially observed due to censoring and systematically bias…