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survdnn

1.0.0Package record

Deep Neural Networks for Survival Analysis with R 'torch'

1packages depend
4Kdownloads / year
2.5%test coverage
13/13flavors OK

Overview

About

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.

Changes in 1.0.0

CRAN resubmission update

  • Milestone release: the package's methods paper is now published in The R Journal (El Badisy 2026, <doi:10.32614/RJ-2026-008>), cited in DESCRIPTION's Description field and a matching inst/CITATION file.
  • Standardized the maintainer's family-name casing to "El Badisy" (title case) in Authors@R, matching the rest of the package suite. Daniel Falbel remains listed as a contributor (ctb).

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 3.0 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-04
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.0.0
READMEYes · 886 wordsVignettesNoNEWSYes · 100% structured · mentions 1.0.0Citation fileYes · cites a publicationWebsitenot declared in DESCRIPTION
Cites an R Journal article
Help pages
18 (2 internal)
Examples that run
0%9 only when donttest examples are enabled (R CMD check --as-cran) · 1 hold no code
Exported functions with examples
50%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
0%

Downloads

4K
CRAN downloads in the past year
Rank #11,468 · ~11/day · ~336/mo
Daily download trend is not available in this view yet.
29630 days
93790 days
4K1 year
Compare downloads with other packages →
Also on111 r2u2 autocran

Repository

6Stars
1Forks
2Open issues
0Open PRs
3Releases
251Commits
2Commit identities
deep-neural-networkssurvival-analysis
251 commits · Last activity 2026-09-19 · 0% stars, 30d · Default branch at 1.0.2, ahead of CRAN 1.0.0 (checked 2026-10-21)
Responsiveness
How these are sampled
PRs merged (all time)
100%
Median days to close, 50 most recently updated closed issues
80
Median days to close, 50 most recently updated closed PRs
0

Stars over time

2025-10-02 · 22026-07-28 · 6
PracticesBeta

5 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/ielbadisy/survdnn on 2026-10-21.

Continuous integration (2)
GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Docs source (1)
README.Rmd
CRAN release process (1)
cran-comments.md
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
12 external dependencies (excludes base and recommended)

Installing survdnn adds 50 packages (26 with compiled code, 38 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, torch 1.9 MB.

Depends (1)
R >= 4.1.0
Imports (13)
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
1direct
0indirect
Imports 1
Depends, Imports or LinkingTo, most downloaded first

People & History

People (2)
Author, Maintainer since 0.6.0 (2025)
Contributor · added in 1.0.0
Releases (6)

Pick two releases to compare their code metrics.

Package metadata

First published
2025-07-22
Total releases
6 / 1 yrs
License
MIT + file LICENSE OSI
Minimum R
≥ 4.1.0
Download size
42 KB

Cite

Cite this package

Run in R for the authors' entry:

citation("survdnn")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.32614/rj-2026-008.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for survdnn version 1.0.0 [Data set]. HJJB, LLC. Data release v2026-10-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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