Optimized ensemble learning framework for neonatal asphyxia prediction using perinatal clinical features.
- DOI
- 10.3389/fpubh.2026.1899811
- Published
- 2026
- Container
- Frontiers in public health
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
uncertain Score 53/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- supportingDirectory of Open Access Journals: A matching record was returned by DOAJ.
- 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.
- supportingOpen access status: Normalized open-access status: open.
- 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.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.3389/fpubh.2026.1899811,
title = {Optimized ensemble learning framework for neonatal asphyxia prediction using perinatal clinical features.},
author = {Afzal M and Amjad M and Ullah S and Shafique R and Amin F and de la Torre I and Ruigómez Noriega A and García Obeso D},
year = {2026},
journal = {Frontiers in public health},
doi = {10.3389/fpubh.2026.1899811},
url = {https://doi.org/10.3389/fpubh.2026.1899811}
}RIS
TY - JOUR TI - Optimized ensemble learning framework for neonatal asphyxia prediction using perinatal clinical features. AU - Afzal M AU - Amjad M AU - Ullah S AU - Shafique R AU - Amin F AU - de la Torre I AU - Ruigómez Noriega A AU - García Obeso D PY - 2026 JO - Frontiers in public health DO - 10.3389/fpubh.2026.1899811 UR - https://doi.org/10.3389/fpubh.2026.1899811 ER -
APA
M, A., M, A., S, U., R, S., F, A., I, D. L. T., A, R. N., & D, G. O. (2026). Optimized ensemble learning framework for neonatal asphyxia prediction using perinatal clinical features.. Frontiers in public health. https://doi.org/10.3389/fpubh.2026.1899811