Enhancing Fairness in Skin Lesion Classification for Medical Diagnosis Using Prune Learning.
- DOI
- 10.1109/jbhi.2026.3652910
- Published
- 2026 Aug
- Container
- IEEE journal of biomedical and health informatics
- Publisher
- Not recorded
- Open access
- unknown
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limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1109/jbhi.2026.3652910,
title = {Enhancing Fairness in Skin Lesion Classification for Medical Diagnosis Using Prune Learning.},
author = {Paxton K and Aslansefat K and Thakker D and Papadopoulos Y and Maslekar T},
year = {2026},
journal = {IEEE journal of biomedical and health informatics},
doi = {10.1109/jbhi.2026.3652910},
url = {https://doi.org/10.1109/jbhi.2026.3652910}
}RIS
TY - JOUR TI - Enhancing Fairness in Skin Lesion Classification for Medical Diagnosis Using Prune Learning. AU - Paxton K AU - Aslansefat K AU - Thakker D AU - Papadopoulos Y AU - Maslekar T PY - 2026 JO - IEEE journal of biomedical and health informatics DO - 10.1109/jbhi.2026.3652910 UR - https://doi.org/10.1109/jbhi.2026.3652910 ER -
APA
K, P., K, A., D, T., Y, P., & T, M. (2026). Enhancing Fairness in Skin Lesion Classification for Medical Diagnosis Using Prune Learning.. IEEE journal of biomedical and health informatics. https://doi.org/10.1109/jbhi.2026.3652910
Source records
- pubmed · retrieved 2026-09-26T20:21:44.309Z