Trustworthy deep learning for malaria diagnosis using explainable artificial intelligence

Rahila Parveen, Baozhi Qui, Wei Song, Nouf Al-Kahtani, Mona M. Jamjoom, Samih M. Mostafa, Nadia Sultan, Joddat Fatima

Open source

DOI
10.1038/s41598-025-28387-7
Published
2025-12-19
Container
Scientific Reports
Publisher
Springer Science and Business Media LLC
Open access
unknown

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BibTeX

@article{allodium:10.1038/s41598-025-28387-7,
  title = {Trustworthy deep learning for malaria diagnosis using explainable artificial intelligence},
  author = {Rahila Parveen and Baozhi Qui and Wei Song and Nouf Al-Kahtani and Mona M. Jamjoom and Samih M. Mostafa and Nadia Sultan and Joddat Fatima},
  year = {2025},
  journal = {Scientific Reports},
  doi = {10.1038/s41598-025-28387-7},
  url = {https://doi.org/10.1038/s41598-025-28387-7}
}

RIS

TY  - JOUR
TI  - Trustworthy deep learning for malaria diagnosis using explainable artificial intelligence
AU  - Rahila Parveen
AU  - Baozhi Qui
AU  - Wei Song
AU  - Nouf Al-Kahtani
AU  - Mona M. Jamjoom
AU  - Samih M. Mostafa
AU  - Nadia Sultan
AU  - Joddat Fatima
PY  - 2025
JO  - Scientific Reports
DO  - 10.1038/s41598-025-28387-7
UR  - https://doi.org/10.1038/s41598-025-28387-7
ER  - 

APA

Parveen, R., Qui, B., Song, W., Al-Kahtani, N., Jamjoom, M. M., Mostafa, S. M., Sultan, N., & Fatima, J. (2025). Trustworthy deep learning for malaria diagnosis using explainable artificial intelligence. Scientific Reports. https://doi.org/10.1038/s41598-025-28387-7

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