Package: survdnn
Title: Deep Neural Networks for Survival Analysis with R 'torch'
Version: 1.0.2
Authors@R: c(
    person(given = "Imad",
           family = "El Badisy",
           email = "elbadisyimad@gmail.com",
           role = c("aut", "cre")),
    person(given = "Daniel",
           family = "Falbel",
           role = "ctb")
    )
Description: 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>. The package is
        described in El Badisy (2026) <doi:10.32614/RJ-2026-008>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: torch, survival, stats, utils, tibble, basetable (>= 1.4.1),
        tidyselect, ggplot2, methods, rsample, cli, glue
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
RoxygenNote: 7.3.3
Config/testthat/edition: 3
BugReports: https://github.com/ielbadisy/survdnn/issues
URL: https://CRAN.R-project.org/package=survdnn
Config/pak/sysreqs: libicu-dev
Repository: https://ielbadisy.r-universe.dev
Date/Publication: 2026-09-19 22:42:43 UTC
RemoteUrl: https://github.com/ielbadisy/survdnn
RemoteRef: HEAD
RemoteSha: 0f0e50df9f575b83ef73e37aa83ae41e351b4091
NeedsCompilation: no
Packaged: 2026-10-28 14:03:41 UTC; root
Author: Imad El Badisy [aut, cre],
  Daniel Falbel [ctb]
Maintainer: Imad El Badisy <elbadisyimad@gmail.com>