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Found 3 papers, 3 papers with code
Discrete-time Competing-Risks Regression with or without Penalization
Additionally, we showcase the utility of our procedure by estimating a survival model for the length of stay of patients hospitalized in the intensive care unit, considering three competing events: discharge to home, transfer to another medical facility, and in-hospital death.
PyDTS: A Python Package for Discrete-Time Survival (Regularized) Regression with Competing Risks
Most methods and software packages for survival regression analysis assume that time is measured on a continuous scale.
Optimal Cox Regression Subsampling Procedure with Rare Events
Massive sized survival datasets are becoming increasingly prevalent with the development of the healthcare industry.
Survival Analysis
Methodology
