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triageR 0.2.0

• Added calibration plots (binned or smoothed) and Brier score to tr_validate(), closing a TRIPOD+AI reporting gap. New calibration_method argument ("binned" or "smooth").
• Calibration plot now included in tr_tripod_report() output.
• Added robustness handling for models with limited probability variation (e.g. tree-based models with many identical predictions).
• Added survival analysis support: tr_fit_survival() (Cox Proportional Hazards and Random Survival Forest via the censored/aorsf engines) and tr_validate_survival() (concordance index / C-index).
• Added tr_launch_app(): an interactive Shiny application for the full triageR workflow (upload data, fit and compare models, validate, explain, review, and download a TRIPOD+AI report) without writing R code.
• Fixed test suite reliability issues related to lazy-loaded survival datasets.

triageR 0.1.1

*PimaIndianDataset in the mlbench package was removed in the latest update, thus the vignette now uses the inbuilt MASS which still has the Pima Indian Diabetes Dataset.

triageR 0.1.0

• Initial development version.
• Added data layer: tr_load_clinical(), tr_check_missing(), tr_impute().
• Added model layer: tr_fit(), tr_validate(), tr_explain().
• Added agent layer: tr_recommend_method(), tr_sensitivity(), tr_agent_review().
• Added reporting layer: tr_tripod_report().

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They may not be fully stable and should be used with caution. We make no claims about them.
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