about.R

library(bslib)

about_card <- card(
  card_header("About the calculator"),
  card_body(
    markdown("
             # **POP-Pe: a sustained opioid use calculator**
             
             **POP-Pe** is a a machine learning tool for **P**rediction of sustained **OP**ioid use in **Pe**diatrics, is was build based on data from the study `Opioid trends and risk factors for sustained use among children and adolescents in Israel: a retrospective cohort study`. Full details regarding the cohort and the data can be found [here](https://journals.lww.com/pain/abstract/9900/opioid_trends_and_risk_factors_for_sustained_use.491.aspx).
             
            The full description of the model fitting procces can be found in our paper [`Prediction of sustained opioid use in children and adolescents using machine learning`](https://www.bjanaesthesia.org/article/S0007-0912(24)00267-8/abstract)

             Three models were train and tested for different follow-up periods: one, two and three years. The one year models had the best discrimination and calibration and thus used for the final model.
             Code can be found on my [GitHub](https://github.com/doratiass/opioid_peds)
             
             This calculator predict the risk of children and adolescence, age 19 and under, who are naive to opioids to devolp a sustained use pattern.
             All demographic characteristics and medical data referese to the preceding year to the first opioid purchase.
             
             The model was trained using `xgboost` and `tidymodels` in `R`, and than calibrated using Shape Constrained Additive Models `scam`.
             
             **NOTICE:** 
             1. This is POC model thus not intended to be used for clinical decision making.
             2. Due to data privacy regulations, the SHAP waterfall plot is presented pre-calibration.
             ")),
  card_footer(markdown("[ObolskiLab](https://uriobols.wixsite.com/obolskilab)"))
)