From ca9c75ea1529063eb4780e5df98a8aae5c0ea17b Mon Sep 17 00:00:00 2001 From: TomMonks Date: Sat, 20 Apr 2024 14:17:13 +0100 Subject: [PATCH] ABOUT: added tutorial paper citation --- pages/3_About.py | 1 + txt/acknowledgement.md | 4 +++- 2 files changed, 4 insertions(+), 1 deletion(-) diff --git a/pages/3_About.py b/pages/3_About.py index 4957f85..4275c5d 100644 --- a/pages/3_About.py +++ b/pages/3_About.py @@ -7,6 +7,7 @@ * Documentation * Researchers via ORCIDs * Sim software +* Simulation + Streamlit Tutorial ( Anything else relevant) ''' diff --git a/txt/acknowledgement.md b/txt/acknowledgement.md index bcbc786..6291083 100644 --- a/txt/acknowledgement.md +++ b/txt/acknowledgement.md @@ -17,6 +17,8 @@ This model is independent research supported by the National Institute for Healt > Detailed model documentation can be found here: https://pythonhealthdatascience.github.io/stars-simpy-example-docs +> Simpy + Streamlit tutorial: https://health-data-science-or.github.io/simpy-streamlit-tutorial + ## Modelling and Simulation Software The model is written in `python3` and `simpy`. The simulation libary `simpy` uses a **process based model worldview**. Given its simplicity it is a highly flexible discrete-event simulation package. @@ -40,6 +42,6 @@ The interactive web application was developed in `streamlit` and deployed freely A beginner tutorial is available to support using `simpy` and `streamlit`. -> Monks, Thomas, & Harper, Alison. (2023). SimPy and StreamLit Tutorial Materials for Healthcare Discrete-Event Simulation (v1.1.0). Zenodo. https://doi.org/10.5281/zenodo.8159080 +> Monks T and Harper A. Improving the usability of open health service delivery simulation models using Python and web apps [version 1; peer review: 1 approved, 2 approved with reservations]. NIHR Open Res 2023, 3:48 (https://doi.org/10.3310/nihropenres.13467.1) > Online interactive tutorial: https://health-data-science-or.github.io/simpy-streamlit-tutorial \ No newline at end of file