New release. Support for left-truncation, recurrent events and competing risks.
ECML PKDD 2020: In this work, we present a very general machine learning framework for time-to-event analysis that uses a data augmentation strategy to reduce complex survival tasks to standard Poisson regression tasks.
R Medicine 2020: The pammtools package for Survival Analysis using Generalized Additive Mixed Models is introduced
ISCB41: The concept of Piece-wise exponential Addtive Mixed Modeling is introduced and its application illustrated using R package pammtools.
mlr3proba: Machine Learning Survival Analysis in R
New paper accepted at ECML PKDD 2020. The paper describes a general machine learning framework for survival analysis.
An R package for probabilistic predictions, including survival analysis.
An R package for Survival Analysis using Generalized Additive Mixed Models
We propose a novel approach for the flexible modeling of complex exposure-lag-response associations in time-to-event data, where multiple past exposures within a defined time window are cumulatively associated with the hazard. Our method allows for …
On the use of piece-wise exponential additive mixed models for the estimation of cumulative effects in survival analysis.