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fairness_eval_ascvd's Introduction

fairness_eval_ascvd

Code to accompany "Evaluating algorithmic fairness in the presence of clinical guidelines: the case of atherosclerotic cardiovascular disease risk estimation. (in press) BMJ Health & Care Informatics, 2022.", by A Foryciarz, SR Pfohl, B Patel and NH Shah.

Setup

pip install -e .

Cohort extraction

Use the fairness_ascvd/scripts/cohort_extraction_script.sh script to preprocess data and extract cohorts.

Experiments

Use the fairness_ascvd/scripts/training_script.sh.sh script to define and run experiments.

Postprocessing and aggregating results

Use the fairness_ascvd/scripts/postprocess_script.sh script to run recalibration, aggregate results, generate original PCE model predictions.

Postprocessing and aggregating results

Use the fairness_ascvd/scripts/evaluation_script.sh script to generate bootstrapped evaluation, and reproduce tables and figures from the paper.

If you find any issues, please email us at [email protected].

fairness_eval_ascvd's People

Contributors

agataf avatar

Stargazers

Nathaniel D Hendrix avatar Siyuan Yan avatar

Watchers

Stephen Pfohl avatar avatar

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