Package: DICErClust
Title: Deep Significance Clustering for Clinical Risk Stratification
Version: 0.1.3
Authors@R: 
    c(person(given="Sarah", family="Ayton", , "sarah.ayton@columbia.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5247-9912")),
    person(given="Yiye", family="Zhang", , "yiz2014@med.cornell.edu", role = c("aut"), comment = c(ORCID = "0000-0003-3494-2699")))
Description: We provide an R implementation of Deep Significance
        Clustering (DICE), a self-supervised learning framework
        designed to identify clinically meaningful and risk-stratified
        patient subgroups from electronic health record (EHR) data.
        DICE jointly optimizes deep representation learning,
        clustering, and outcome prediction while enforcing statistical
        significance between predicted outcomes and cluster membership.
        This integrated optimization produces subgroups that are both
        clinically coherent and predictive, addressing a gap where
        traditional unsupervised clustering methods and supervised risk
        prediction models alone may fail to generate actionable
        clinical groupings. See Huang et al. (2021)
        <doi:10.1093/jamia/ocab203>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: argparser, ggplot2, torch, pROC
Suggests: knitr, rmarkdown, scales
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-07-09 14:23:49 UTC; root
Author: Sarah Ayton [aut, cre] (ORCID:
        <https://orcid.org/0000-0001-5247-9912>), Yiye Zhang [aut]
        (ORCID: <https://orcid.org/0000-0003-3494-2699>)
Maintainer: Sarah Ayton <sarah.ayton@columbia.edu>
Config/roxygen2/version: 8.0.0
Repository: https://cran.r-universe.dev
Date/Publication: 2026-07-08 18:10:08 UTC
RemoteUrl: https://github.com/cran/DICErClust
RemoteRef: HEAD
RemoteSha: e1bd5047df2e3b6928916fa0bdadd0805440b88b