Is a racially-biased algorithm delaying health care for one million Black people?
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Even small biases in widely used algorithms can have serious consequences.
“Even small biases in widely used algorithms can have serious consequences [57].”
From Ethical Considerations of Using ChatGPT in Health Care (2023) · cites this paper as [57]
Cites
Levey, A. S., Bosch, J. P., Lewis, J. B., Greene, T., Rogers, N., Roth, D., & for the Modification of Diet in Renal Disease Study Group* (1999) · Annals of Internal Medicine · doi:10.7326/0003-4819-130-6-199903160-00002 · Cited by 15,079 · see citing works
Clinical Implications of Removing Race From Estimates of Kidney Function
Diao, J. A., Wu, G. J., Taylor, H. A., Tucker, J. K., Powe, N. R., Kohane, I. S., & Manrai, A. K. (2020) · JAMA · doi:10.1001/jama.2020.22124 · Cited by 125 · see citing works
Inker, L. A., Couture, S. J., Tighiouart, H., Abraham, A. G., Beck, G. J., Feldman, H. I., Greene, T., Gudnason, V. G., Karger, A. B., Eckfeldt, J. H., et al. (2020) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2020.11.005 · Cited by 78 · see citing works
Peralta, C. A., RISCH, N. J., Lin, F., et al. (2009) · American Journal of Nephrology · doi:10.1159/000268955 · Cited by 48 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Ethical Considerations of Using ChatGPT in Health Care
Wang, C., Liu, S., Yang, H., Guo, J., Wu, Y., & Liu, J. (2023) · Journal of Medical Internet Research · doi:10.2196/48009 · Cited by 541 · see citing works
Artificial Intelligence in Medicine & ChatGPT: De-Tether the Physician
DiGiorgio, A. M., & Ehrenfeld, J. M. (2023) · Journal of Medical Systems · doi:10.1007/s10916-023-01926-3 · Cited by 82 · see citing works
- Authors
- Madhusoodanan, J.
- Corresponding author
- Madhusoodanan, Jyoti
- Venue
- Nature
- Published
- 2020-12-16
- Volume
- 588
- Issue
- 7839
- Pages
- 546-547
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W3112849752
- Cited by
- 13
- References
- 4
- Citations by year
- 2025: 1 · 2023: 5 · 2022: 4 · 2021: 3
- Type
- other
- Language
- en
- Open access
- closed
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Keywords
- algorithmic bias, racial bias, health care access, Black patients, health care disparities, algorithmic decision-making
- MeSH terms
- Algorithms, Black or African American, Creatinine, Delivery of Health Care, Glomerular Filtration Rate, Humans, Kidney Diseases, Reproducibility of Results, Racism
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
