Multi-scenario evaluation of federated learning for privacy-preserving malaria prediction with Ghana DHS data.

Kovor DK, Osei EO

DOI: 10.1371/journal.pdig.0001581
Published: 2026 Jul
Container: PLOS digital health
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pdig.0001581,
  title = {Multi-scenario evaluation of federated learning for privacy-preserving malaria prediction with Ghana DHS data.},
  author = {Kovor DK and Osei EO},
  year = {2026},
  journal = {PLOS digital health},
  doi = {10.1371/journal.pdig.0001581},
  url = {https://doi.org/10.1371/journal.pdig.0001581}
}

RIS

TY  - JOUR
TI  - Multi-scenario evaluation of federated learning for privacy-preserving malaria prediction with Ghana DHS data.
AU  - Kovor DK
AU  - Osei EO
PY  - 2026
JO  - PLOS digital health
DO  - 10.1371/journal.pdig.0001581
UR  - https://doi.org/10.1371/journal.pdig.0001581
ER  -

APA

DK, K., & EO, O. (2026). Multi-scenario evaluation of federated learning for privacy-preserving malaria prediction with Ghana DHS data.. PLOS digital health. https://doi.org/10.1371/journal.pdig.0001581

Source records

pubmed · retrieved 2026-09-27T07:28:54.038Z