Predicting public Intensive care unit mortality and hospitalization using Data: An evaluation of Brazil’s Largest COVID-19 epidemiological dataset
- DOI
- 10.1016/j.iccn.2026.104363
- Published
- 2026-08
- Container
- Intensive and Critical Care Nursing
- Publisher
- Elsevier BV
- 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:10.1016/j.iccn.2026.104363,
title = {Predicting public Intensive care unit mortality and hospitalization using Data: An evaluation of Brazil’s Largest COVID-19 epidemiological dataset},
author = {Lia da Graça and João Paulo de Oliveira and Aratã Saraiva and Richarlisson Borges de Morais and Monica Taminato and Hugo Fernandes and Germán González},
year = {2026},
journal = {Intensive and Critical Care Nursing},
doi = {10.1016/j.iccn.2026.104363},
url = {https://doi.org/10.1016/j.iccn.2026.104363}
}RIS
TY - JOUR TI - Predicting public Intensive care unit mortality and hospitalization using Data: An evaluation of Brazil’s Largest COVID-19 epidemiological dataset AU - Lia da Graça AU - João Paulo de Oliveira AU - Aratã Saraiva AU - Richarlisson Borges de Morais AU - Monica Taminato AU - Hugo Fernandes AU - Germán González PY - 2026 JO - Intensive and Critical Care Nursing DO - 10.1016/j.iccn.2026.104363 UR - https://doi.org/10.1016/j.iccn.2026.104363 ER -
APA
Graça, L. D., Oliveira, J. P. D., Saraiva, A., Morais, R. B. D., Taminato, M., Fernandes, H., & González, G. (2026). Predicting public Intensive care unit mortality and hospitalization using Data: An evaluation of Brazil’s Largest COVID-19 epidemiological dataset. Intensive and Critical Care Nursing. https://doi.org/10.1016/j.iccn.2026.104363
Source records
- crossref · retrieved 2026-09-25T18:52:22.258Z