SLOS
ICU Length of Stay Prediction and Efficiency Evaluation
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.1 |
rolling linux/jammy R-4.5 | SLOS_1.0.1.tar.gz |
48.9 KiB |
1.0.1 |
rolling linux/noble R-4.5 | SLOS_1.0.1.tar.gz |
48.8 KiB |
1.0.1 |
rolling source/ R- | SLOS_1.0.1.tar.gz |
35.5 KiB |
1.0.1 |
latest linux/jammy R-4.5 | SLOS_1.0.1.tar.gz |
48.9 KiB |
1.0.1 |
latest linux/noble R-4.5 | SLOS_1.0.1.tar.gz |
48.8 KiB |
1.0.1 |
latest source/ R- | SLOS_1.0.1.tar.gz |
35.5 KiB |
1.0.1 |
2026-04-26 source/ R- | SLOS_1.0.1.tar.gz |
35.5 KiB |
1.0.1 |
2026-04-23 source/ R- | SLOS_1.0.1.tar.gz |
35.5 KiB |
1.0.1 |
2026-04-09 windows/windows R-4.5 | SLOS_1.0.1.zip |
51.7 KiB |
1.0.1 |
2025-04-20 source/ R- | SLOS_1.0.1.tar.gz |
35.5 KiB |