Package: CRBHSF 0.1.0
CRBHSF: Cyber-Resilient Bayesian Healthcare Surveillance Framework
Provides methods for cyber-resilient healthcare performance surveillance using Bayesian risk estimation, latent organisational trust modelling, cyber-resilience assessment, external validation, decision-theoretic optimisation, and digital-twin deployment simulation. The package supports prospective deterioration monitoring, uncertainty-aware risk assessment, intervention prioritisation, ablation analysis, and operational evaluation for healthcare performance management and health system resilience research. The methodological framework is informed by contemporary guidance on prediction model development and validation (Efthimiou et al., 2024 <doi:10.1136/bmj-2023-078276>), transparent reporting of prediction models (Collins et al., 2024 <doi:10.1136/bmj-2023-078378>), and decision-analytic model evaluation (Vickers and Elkin, 2006 <doi:10.1177/0272989X06295361>).
Authors:
CRBHSF_0.1.0.tar.gz
CRBHSF_0.1.0.zip(r-4.7-any)CRBHSF_0.1.0.zip(r-4.6-any)CRBHSF_0.1.0.zip(r-4.5-any)
CRBHSF_0.1.0.tgz(r-4.6-any)CRBHSF_0.1.0.tgz(r-4.5-any)
CRBHSF_0.1.0.tar.gz(r-4.7-any)CRBHSF_0.1.0.tar.gz(r-4.6-any)
CRBHSF_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
CRBHSF/json (API)
| # Install 'CRBHSF' in R: |
| install.packages('CRBHSF', repos = c('https://zerish12.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/zerish12/crbhsf/issues
bayesian-surveillancecyber-resiliencedecision-supportdigital-healthdigital-twinhealth-data-science-sandboxhealthcare-analytics
Last updated from:fcf9b20058. Checks:7 WARNING, 1 ERROR, 1 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | WARNING | 139 | ||
| source / vignettes | ERROR | 177 | ||
| linux-release | WARNING | 123 | ||
| macos-release | WARNING | 102 | ||
| macos-oldrel | WARNING | 77 | ||
| windows-devel | WARNING | 63 | ||
| windows-release | WARNING | 70 | ||
| windows-oldrel | WARNING | 56 | ||
| wasm-release | OK | 106 |
Exports:clean_health_datacompare_ml_benchmarkscompute_crbhsf_riskcompute_crprcreate_deterioration_outcomeestimate_evibestimate_latent_trustfit_bayesian_surveillancegenerate_surveillance_reportplot_ablation_aucplot_deployment_impactplot_risk_distributionrun_ablation_studysimulate_digital_twinvalidate_surveillance
Dependencies:clicpp11dplyrfarvergenericsggplot2gluegtableisobandlabelinglifecyclemagrittrpillarpkgconfigpROCpurrrR6RColorBrewerRcpprlangS7scalestibbletidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Clean healthcare surveillance data | clean_health_data |
| Compare simple machine-learning benchmarks | compare_ml_benchmarks |
| Compute CRBHSF risk score | compute_crbhsf_risk |
| Compute Cyber-Resilience Pressure Ratio | compute_crpr |
| Create future deterioration outcome | create_deterioration_outcome |
| Estimate expected value of intervention benefit | estimate_evib |
| Estimate latent organisational trust | estimate_latent_trust |
| Fit lightweight Bayesian surveillance model | fit_bayesian_surveillance |
| Generate simple surveillance report | generate_surveillance_report |
| Plot ablation AUC | plot_ablation_auc |
| Plot digital-twin deployment impact | plot_deployment_impact |
| Plot risk distribution | plot_risk_distribution |
| Run CRBHSF ablation study | run_ablation_study |
| Simulate digital-twin deployment | simulate_digital_twin |
| Validate surveillance score | validate_surveillance |