Reproducible Healthcare Simulations in Python and R
For the UKRI-funded project STARS: Sharing Tools and Artefacts for Reproducible Simulations
Pinned Repositories
intro-open-sim
An introduction to building open Descrete-Event Simulation (DES) in Python
stars-eom-rcc
Modifications to the "Exeter Oncology Model: Renal Cell Carcinoma edition (EOM-RCC)" as part of STARS work package 3.
stars-logo
STARS branding
stars-publications
A list of all STARS publications including journals articles, conference papers, book chapters, pre-prints and presentations
stars-reproduce-allen-2020
Test-run of our reproducibility protocol on Allen et al. 2020: "A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic"
stars-reproduce-kim-2021
Assessing the computational reproducibility of Kim et al. 2021 as part of STARS.
stars-shiny-simmer
WORK IN PROGRESS: An example R shiny interface to a simmer DES model.
stars-simpy-jupterlite
A template for Discrete-Event Simulation (DES) repositories that use JupyerLite and xeus-python to enable reproducible environments and models
stars-treat-simmer
R Simmer implemention of the treatment simulation model
stars_reproduction_template
Template repository for assessing the computational reproducibility of simulation studies on STARS
Reproducible Healthcare Simulations in Python and R's Repositories
pythonhealthdatascience/stars-eom-rcc
Modifications to the "Exeter Oncology Model: Renal Cell Carcinoma edition (EOM-RCC)" as part of STARS work package 3.
pythonhealthdatascience/stars-shiny-simmer
WORK IN PROGRESS: An example R shiny interface to a simmer DES model.
pythonhealthdatascience/stars-simpy-jupterlite
A template for Discrete-Event Simulation (DES) repositories that use JupyerLite and xeus-python to enable reproducible environments and models
pythonhealthdatascience/intro-open-sim
An introduction to building open Descrete-Event Simulation (DES) in Python
pythonhealthdatascience/stars-logo
STARS branding
pythonhealthdatascience/stars-reproduce-allen-2020
Test-run of our reproducibility protocol on Allen et al. 2020: "A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic"
pythonhealthdatascience/stars-reproduce-kim-2021
Assessing the computational reproducibility of Kim et al. 2021 as part of STARS.
pythonhealthdatascience/stars-treat-simmer
R Simmer implemention of the treatment simulation model
pythonhealthdatascience/introductory_foss_sim_tutorial_paper
Building Discrete-Event Simulation Models in Free and Open Source Software: An Introductory Tutorial (paper)
pythonhealthdatascience/stars-ciw-example
A treatment simulation model implemented in CiW
pythonhealthdatascience/stars-simpy-example-docs
STARS Project: Example `simpy` model documentation using JupyterBook, GitHub Pages, and STRESS
pythonhealthdatascience/stars-stlite-example
STARS Project: deploying a python DES model using stlite
pythonhealthdatascience/stars_reproduction_template
Template repository for assessing the computational reproducibility of simulation studies on STARS
pythonhealthdatascience/stars_wp1_summary
Summary of the eight computational reproducibility assessments conducted as part of STARS Work Package 1. These assessed discrete-event simulation papers with models in Python and R.
pythonhealthdatascience/stress_update
A review and update of the Strengthening the Reporting of Empirical Simulation Studies guidelines for DES, SD, and ABS.
pythonhealthdatascience/.github
GitHub profile
pythonhealthdatascience/stars-reproduce-lim-2020
Assessing the computational reproducibility of Lim et al. 2020 as part of STARS.
pythonhealthdatascience/stars-streamlit-example
STARS Project: deploying a python DES model using streamlit
pythonhealthdatascience/stars-treat-sim
Implementation of python package for Nelson's (2013) treatment centre model
pythonhealthdatascience/stars_reproduction_protocol
Syncs with Overleaf Latex protocol on simulation reproduction
pythonhealthdatascience/jackson-network-jupyterlite
pythonhealthdatascience/pythonhealthdatascience.r-universe.dev
R universe management for STARS
pythonhealthdatascience/stars-reproduce-anagnostou-2022
Assessing the computational reproducibility of Anagnostou et al. 2022 as part of STARS.
pythonhealthdatascience/stars-reproduce-hernandez-2015
Assessing the computational reproducibility of Hernandez et al. 2015 as part of STARS.
pythonhealthdatascience/stars-reproduce-huang-2019
Assessing the computational reproducibility of Huang et al. 2019 as part of STARS.
pythonhealthdatascience/stars-reproduce-johnson-2021
Assessing the computational reproducibility of Johnson et al. 2021 as part of STARS.
pythonhealthdatascience/stars-reproduce-shoaib-2022
Assessing the computational reproducibility of Shoaib and Ramamohan 2022 as part of STARS.
pythonhealthdatascience/stars-reproduce-wood-2021
Assessing the computational reproducibility of Wood et al. 2021 as part of STARS.
pythonhealthdatascience/stars-treat-simmer-quarto-wasm
WASM deployed implementation of https://github.com/pythonhealthdatascience/stars-treat-simmer using Quarto Live
pythonhealthdatascience/stars_wp3_summary
Reflections from prospective and retrospective application of the STARS framework