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>.

Getting started

Package details

AuthorImad EL BADISY [aut, cre]
MaintainerImad EL BADISY <elbadisyimad@gmail.com>
LicenseMIT + file LICENSE
Version0.7.5
URL https://github.com/ielbadisy/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 Jan. 8, 2026, 9:07 a.m.