Provides tools for predicting ICU length of stay and assessing ICU efficiency. It is based on the methodologies proposed by Peres et al. (2022, 2023), which utilize data-driven approaches for modeling and validation, offering insights into ICU performance and patient outcomes. References: Peres et al. (2022)<https://pubmed.ncbi.nlm.nih.gov/35988701/>, Peres et al. (2023)<https://pubmed.ncbi.nlm.nih.gov/37922007/>. More information: <https://github.com/igor-peres/ICU-Length-of-Stay-Prediction>.
Version: | 1.0.0 |
Depends: | R (≥ 3.5.0) |
Imports: | httr, MLmetrics, ems, dplyr, ggplot2, magrittr, caretEnsemble, ranger |
Suggests: | testthat |
Published: | 2025-01-20 |
DOI: | 10.32614/CRAN.package.SLOS |
Author: | Igor Peres [aut], Joana da Matta [cre] |
Maintainer: | Joana da Matta <joana.damatta02 at gmail.com> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
CRAN checks: | SLOS results |
Reference manual: | SLOS.pdf |
Package source: | SLOS_1.0.0.tar.gz |
Windows binaries: | r-devel: not available, r-release: SLOS_1.0.0.zip, r-oldrel: not available |
macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available |
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