Implementations of classical and machine learning models for survival analysis, including deep neural networks via 'keras' and 'tensorflow'. Each model includes a separated fit and predict interface with consistent prediction types for predicting risk or survival probabilities. Models are either implemented from 'Python' via 'reticulate' <https://CRAN.R-project.org/package=reticulate>, from code in GitHub packages, or novel implementations using 'Rcpp' <https://CRAN.R-project.org/package=Rcpp>. Neural networks are implemented from the 'Python' package 'pycox' <https://github.com/havakv/pycox>.
[email protected] is safe to use (health: 49/100)
Get this data programmatically — free, no authentication.
curl https://depscope.dev/api/check/conda/r-survivalmodelsFirst published · 2022-04-26 17:47:24.710000+00:00
Last updated · 2025-09-23 00:59:55.752000+00:00