Surgical Forecasting Tool

A forecasting tool designed to support surgical scheduling and capacity planning within healthcare settings. This project leverages data science techniques to predict surgical demand and optimize resource allocation.

📦 Repository Structure

• data/: Contains input datasets used for modeling and evaluation.
• results/: Output files including forecasts and performance metrics.
• surgical_sim/: Contains the code used to power the simulation.
• experiment_scenarios.ipynb: Contains code used to create the results files.
• data_analysis_validation.ipynb: Contains code used to validate the simulation.
• sim_validation.ipynb: Further validation using full random selection.
• results_analysis.ipynb: Analysis of results.
• simulation_framework_simpy.ipynb: Rough workings used to create the module.
• simulation_parameterisation.ipynb: Processing of the parameterisation data.

🛠️ Installation

# Clone the repository
git clone https://github.com/CSampsonSomersetFT/SurgicalForecastingTool.git
cd SurgicalForecastingTool

# (Optional) Create a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

# Install dependencies
pip install -r requirements.txt