Dataset effects outweigh algorithmic effects in determining fairness of healthcare machine learning.

Elgendi M, Elkhalifa A, Khandoker A, Maruotti A, Zhou H, Menon C, Ward R

DOI: 10.1038/s41746-026-02723-1
Published: 2026 May 13
Container: NPJ digital medicine
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1038/s41746-026-02723-1,
  title = {Dataset effects outweigh algorithmic effects in determining fairness of healthcare machine learning.},
  author = {Elgendi M and Elkhalifa A and Khandoker A and Maruotti A and Zhou H and Menon C and Ward R},
  year = {2026},
  journal = {NPJ digital medicine},
  doi = {10.1038/s41746-026-02723-1},
  url = {https://doi.org/10.1038/s41746-026-02723-1}
}

RIS

TY  - JOUR
TI  - Dataset effects outweigh algorithmic effects in determining fairness of healthcare machine learning.
AU  - Elgendi M
AU  - Elkhalifa A
AU  - Khandoker A
AU  - Maruotti A
AU  - Zhou H
AU  - Menon C
AU  - Ward R
PY  - 2026
JO  - NPJ digital medicine
DO  - 10.1038/s41746-026-02723-1
UR  - https://doi.org/10.1038/s41746-026-02723-1
ER  -

APA

M, E., A, E., A, K., A, M., H, Z., C, M., & R, W. (2026). Dataset effects outweigh algorithmic effects in determining fairness of healthcare machine learning.. NPJ digital medicine. https://doi.org/10.1038/s41746-026-02723-1

Source records

pubmed · retrieved 2026-09-25T18:54:01.669Z