This repository contains the code and sample data used for the research work titled "Percent lung involved with tuberculosis on chest X-ray predicts unfavorable treatment outcome and is accurately predicted with artificial intelligence". More information on the raw data used for this research work is present in the TB-Portals website (https://tbportals.niaid.nih.gov).
data/: Contains the example data files used for the analysis.models/: Ensemble model weights.notebooks/: Jupyter notebooks for cohort selection, quality checking and data exploration.scripts/: Python scripts for regression and classification tasks.requirements.txt: Python dependencies required to run the scripts.LICENSE: License information.
- Python 3.7 or higher
- Git
- Virtual environment tools (optional)
- Clone the repository:
git clone https://github.com/farhat-lab/tbp-severity-scoring.git
cd tbp-severity-scoring- Create and activate a virtual environment (optional but recommended):
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`- Install the required dependencies:
pip install -r requirements.txtTo test the PLI regression model on your image samples:
python scripts/test.pyThe model weights are deposited for peer-review purposes only. See LICENSE file for more details.