triageR: Automated Machine Learning and AI Agent Tools for Clinical Prediction Modelling

Provides a streamlined workflow for building, validating, and reporting clinical prediction models. Combines standard machine learning tools with an optional AI agent that recommends appropriate statistical methods, runs sensitivity analyses, and flags common pitfalls. Includes automated generation of reports aligned with TRIPOD+AI reporting guidance (Collins et al. (2024 <doi:10.1136/bmj-2023-078378>)) for reproducible, guideline-aligned research.

Version:	0.1.1
Depends:	R (≥ 4.1.0)
Imports:	DALEX, dplyr, ellmer, ggplot2, mice, naniar, parsnip, pROC, quarto, recipes, tibble, tidyr, workflows, yardstick
Suggests:	knitr, rmarkdown, mlbench, missForest, ranger, spelling, testthat (≥ 3.0.0), xgboost, MASS
Published:	2026-08-02
DOI:	10.32614/CRAN.package.triageR
Author:	Uwakmfon Paul [aut, cre, cph]
Maintainer:	Uwakmfon Paul <uwakmfon31 at gmail.com>
BugReports:	https://github.com/DevWebWacky/triageR/issues
License:	MIT + file LICENSE
URL:	https://github.com/DevWebWacky/triageR
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	triageR results

Documentation:

Reference manual:	triageR.html , triageR.pdf
Vignettes:	Case Study: Breast Cancer Diagnosis (source, R code) Introduction to triageR (source, R code)

Downloads:

Package source:	triageR_0.1.1.tar.gz
Windows binaries:	r-devel: triageR_0.1.1.zip, r-release: triageR_0.1.1.zip, r-oldrel: triageR_0.1.1.zip
macOS binaries:	r-release (arm64): triageR_0.1.1.tgz, r-oldrel (arm64): triageR_0.1.1.tgz, r-release (x86_64): triageR_0.1.1.tgz, r-oldrel (x86_64): triageR_0.1.1.tgz
Old sources:	triageR archive

Linking:

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