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DeSurv
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README.md
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DeSurv
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Welcome to the repository for "Derivative-Based Neural Modelling of Cumulative Distribution Functions for Survival Analysis", to appear at AISTATS 2022. ## Getting started Create a virtual environment and activate it: ``` python -m venv desurv_env source desurv_env/bin/activate ``` Install dependencies: ``` python -m pip install -r requirements.txt ``` Access the source code: ``` cd src ``` Use DeCDF for CDF/density estimation: ``` python -m jupyter notebook fig2.ipynb ``` Train a DeSurv model: ``` python desurv.py ``` ### Additional info: The core code components of DeCDF/DeSurv can be found in `classes.py`. The `ODESurvSingle` class implements a DeSurv model for the single-risk setting. The `ODESurvMultiple` class implements a DeSurv model for the competing-risk setting. `desurv.py` illustrates how a DeSurv model can be trained and is designed to be easily adaptable to a typical user's problem setting. `fig2.ipynb` illustrates the basic concept behind DeCDF and hence DeSurv in an interactive setting. ### Acknowledgements We would like to acknowledge the [pycox](https://github.com/havakv/pycox) library of Kvamme et al. for its excellent dataset, model and evaluation provisions which proved very useful when undertaking this project.
