survdnn: Deep Neural Networks for Survival Analysis Using 'torch'
Provides deep learning models for right-censored survival data using the 'torch' backend. Supports multiple loss functions, including Cox partial likelihood, L2-penalized Cox, time-dependent Cox, and accelerated failure time (AFT) loss. Offers a formula-based interface, built-in support for cross-validation, hyperparameter tuning, survival curve plotting, and evaluation metrics such as the C-index, Brier score, and integrated Brier score. For methodological details, see Kvamme et al. (2019) <https://www.jmlr.org/papers/v20/18-424.html>.
| Version: | 0.6.3 |
| Depends: | R (≥ 4.1.0) |
| Imports: | torch,survival, stats, utils,tibble,dplyr,purrr,tidyr,ggplot2, methods,rsample,cli,glue |
| Suggests: | testthat (≥ 3.0.0),knitr,rmarkdown |
| Published: | 2025-10-30 |
| DOI: | 10.32614/CRAN.package.survdnn |
| Author: | Imad EL BADISY [aut, cre] |
| Maintainer: | Imad EL BADISY <elbadisyimad at gmail.com> |
| BugReports: | https://github.com/ielbadisy/survdnn/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/ielbadisy/survdnn |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| CRAN checks: | survdnn results |
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