survdnn: Deep Neural Networks for Survival Analysis with R '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>. The package is described in El Badisy (2026) <doi:10.32614/RJ-2026-008>.

Getting started

Package details

AuthorImad El Badisy [aut, cre], Daniel Falbel [ctb]
MaintainerImad El Badisy <elbadisyimad@gmail.com>
LicenseMIT + file LICENSE
Version1.0.0
URL https://CRAN.R-project.org/package=survdnn 
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("survdnn")

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survdnn documentation built on Aug. 22, 2026, 5:06 p.m.