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survdnn

0.7.6

Deep Neural Networks for Survival Analysis with R 'torch'

1packages depend
3.7Kdownloads / year
2.5%test coverage
13/13checks pass

Overview

About
Maintained by Imad EL BADISYFirst published 2025-07-225 releasesCRAN page ↗GitHub ↗

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.

Install

Health

CRAN checks
13OK
Slowest check: 3.1 min · r-oldrel-macos-x86_64
Code health
Yes
Tests · ratio 0.48
2.5%
Coverage · measured lines
100%
Documentation · exports
13
Dependencies · direct
Check history
  • OK2026-08-04
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 887 wordsVignettesNopkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
10%
Documented parameters
100%
Return-value docs
100%
References docs
0%

Downloads

3.7K
CRAN downloads in the past year
Rank #8,510 · ~10/day · ~304/mo
Daily download trend is not available in this view yet.
24830 days
1.1K90 days
3.7K1 year
Compare downloads with other packages →
Also on116 r2u18 autocran

Repository

Repository
6Stars
1Forks
2Open issues
0Open PRs
3Releases
243Commits
2Contributors
deep-neural-networkssurvival-analysis
243 commits · Last activity 2026-08-20 · +20% stars, 30d

Stars over time

2025-08-23 · 12026-07-28 · 6

Repository practices

Upstream repositoryBeta

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

Checks run against github.com/ielbadisy/survdnn on 2026-08-16.

Continuous integration (1)
GitHub Actions
CRAN release process (1)
cran-comments.md
Docs source (1)
README.Rmd
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
12 external dependencies (excludes base and recommended)
Depends (1)
R >= 4.1.0
Imports (13)
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
1direct
0indirect

Code & Tests

People & History

People (1)
Maintainer (1)
Author, Maintainer
Authors (1)
Author, Maintainer
Package Timeline

5 releases. Pick two to compare their code metrics. R releases are shown for context.

  • 0.7.6Latest
    2026-04-29 · current release · diff ↗
  • R
    R 4.6.0 released · 2026-04-24
  • 0.7.5
    2026-01-08 · diff ↗
  • 0.7.0
    2025-12-23 · diff ↗
  • 0.6.3
    2025-10-30 · diff ↗
  • 0.6.0
    2025-07-22
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2025-07-22
Total releases
5 / 1 yrs
License
MIT + file LICENSE OSI
Minimum R
≥ 4.1.0
Download size
41 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("survdnn")
EL BADISY, I. (2026). survdnn: Deep Neural Networks for Survival Analysis with R 'torch' (Version 0.7.6) [Computer software]. https://doi.org/10.32614/CRAN.package.survdnn

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

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 0.7.6 [Data set]. HJJB, LLC. Data release v2026-08-21. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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