Fairness aware subset selection for advancing equity in skin cancer detection
Strategic data selection is critical for equitable AI-driven diagnostics. FAIR-SCAN advances fairness and accuracy in skin cancer detection, supporting development of trustworthy clinical AI systems.
Authors
- Bahar Dasgeb (ORCID: https://orcid.org/0000-0002-8185-1821)
- Yehuda Perry (ORCID: https://orcid.org/0009-0001-5414-0119)
- D.J. Foran
- Abdulaziz A Almuzaini
- Vivek K Singh
- Adewole S Adamson
Institutions
- Rutgers, The State University of New Jersey (US)
- Rutgers Sexual and Reproductive Health and Rights (NL)
- Islamic University of Madinah (SA)
- The University of Texas at Austin (US)
Publication Details
- Journal
- Journal of the American Medical Informatics Association
- Published
- 2026-02-18
- DOI
- https://doi.org/10.1093/jamia/ocag028
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00