A federated attention-based stacked LSTM framework for interpretable malaria diagnosis under simulated non-IID federated conditions
- DOI
- 10.1038/s41598-026-62791-x
- Published
- 2026-07-17
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-62791-x,
title = {A federated attention-based stacked LSTM framework for interpretable malaria diagnosis under simulated non-IID federated conditions},
author = {Sangeetha Murugan and K. Thirunadanasikamani and Komal Kumar Napa and Haiter Lenin Allasi and S. Sathya and G. Geethamahalakshmi and Rajkumar Govindarajan and Mary Vasanthi Soosaimariyan},
year = {2026},
journal = {Scientific Reports},
doi = {10.1038/s41598-026-62791-x},
url = {https://doi.org/10.1038/s41598-026-62791-x}
}RIS
TY - JOUR TI - A federated attention-based stacked LSTM framework for interpretable malaria diagnosis under simulated non-IID federated conditions AU - Sangeetha Murugan AU - K. Thirunadanasikamani AU - Komal Kumar Napa AU - Haiter Lenin Allasi AU - S. Sathya AU - G. Geethamahalakshmi AU - Rajkumar Govindarajan AU - Mary Vasanthi Soosaimariyan PY - 2026 JO - Scientific Reports DO - 10.1038/s41598-026-62791-x UR - https://doi.org/10.1038/s41598-026-62791-x ER -
APA
Murugan, S., Thirunadanasikamani, K., Napa, K. K., Allasi, H. L., Sathya, S., Geethamahalakshmi, G., Govindarajan, R., & Soosaimariyan, M. V. (2026). A federated attention-based stacked LSTM framework for interpretable malaria diagnosis under simulated non-IID federated conditions. Scientific Reports. https://doi.org/10.1038/s41598-026-62791-x
Source records
- crossref · retrieved 2026-09-26T02:29:35.766Z