Race and Mistrust in End-of-Life Care
Short workshop paper (FAT/ML 2018): https://arxiv.org/abs/1807.00124
@article{boag-fatml2018,
title={Modeling Mistrust in End-of-Life Care},
author={W. Boag and H. Suresh and L.A. Celi and P. Szolovits and M. Ghassemi},
publisher={Fairness, Accountability, and Transparency in Machine Learning (FAT/ML 2018) workshop},
year={2018}
}
15-page conference paper (MLHC 2018): https://arxiv.org/abs/1808.03827
@InProceedings{boag-mistrust2018,
title = {Racial Disparities and Mistrust in End-of-Life Care},
author = {Boag, W. and Suresh, H. and Celi, L.A. and Szolovits, P. and Ghassemi, M.},
booktitle = {Proceedings of the 3rd Machine Learning for Healthcare Conference},
pages = {587--602},
year = {2018},
volume = {85},
series = {Proceedings of Machine Learning Research},
address = {Palo Alto, California},
month = {17--18 Aug},
publisher = {PMLR},
pdf = {http://proceedings.mlr.press/v85/boag18a/boag18a.pdf},
url = {http://proceedings.mlr.press/v85/boag18a.html},
}
Masters Thesis: https://willieboag.files.wordpress.com/2018/05/wboag-masters.pdf
@MastersThesis{boag-thesis2018,
title={Quantifying Racial Disparities in End-of-Life Care},
author={W. Boag},
school={MIT},
year={2018}
}
The code folder has 6 notebooks:
1. race_mimic_aggressive.ipynb: Generate the figures for race-based treatment disparities in MIMIC
2. trust.ipynb: Generates the various mistrust metric proxies and saves them to file.
3. mistrust_mimic_aggressive.ipynb: Generate the figures for mistrust-based treatment disparities in MIMIC
4. cohort.ipynb: Generate additional stats (e.g. table one, pairwise comparisons of metrics & severity score, etc)
5. outcomes_ml.ipynb: Uses trust-based features to improve predictions for clinical tasks.
6. race_eicu_aggressive.ipynb: Generate the figures for race-based treatment disparities in eICU
Run trust.ipynb before running:
- mistrust_mimic_aggressive.ipynb
- cohort.ipynb
- outcomes_ml.ipynb