The Challenges of Predicting Rare Outcomes: A Critical Appraisal of Machine Learning Using the Pediatric Resuscitation and Trauma Outcome (PRESTO) Model in a Tanzanian Injury Registry
- DOI
- 10.1002/wjs.70553
- Published
- 2026-09-03
- Container
- World Journal of Surgery
- Publisher
- Wiley
- 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:10.1002/wjs.70553,
title = {The Challenges of Predicting Rare Outcomes: A Critical Appraisal of Machine Learning Using the Pediatric Resuscitation and Trauma Outcome (PRESTO) Model in a Tanzanian Injury Registry},
author = {Joao Vitor Perez de Souza and Elizabeth M. Keating and William Nkenguye and Rosalia Njau and Happiness Kajoka and Pollyana Coelho Pessoa Santos and Edwin Joseph Shewiyo and Catherine A. Staton and Blandina T. Mmbaga and Joao Ricardo Nickenig Vissoci},
year = {2026},
journal = {World Journal of Surgery},
doi = {10.1002/wjs.70553},
url = {https://doi.org/10.1002/wjs.70553}
}RIS
TY - JOUR TI - The Challenges of Predicting Rare Outcomes: A Critical Appraisal of Machine Learning Using the Pediatric Resuscitation and Trauma Outcome (PRESTO) Model in a Tanzanian Injury Registry AU - Joao Vitor Perez de Souza AU - Elizabeth M. Keating AU - William Nkenguye AU - Rosalia Njau AU - Happiness Kajoka AU - Pollyana Coelho Pessoa Santos AU - Edwin Joseph Shewiyo AU - Catherine A. Staton AU - Blandina T. Mmbaga AU - Joao Ricardo Nickenig Vissoci PY - 2026 JO - World Journal of Surgery DO - 10.1002/wjs.70553 UR - https://doi.org/10.1002/wjs.70553 ER -
APA
Souza, J. V. P. D., Keating, E. M., Nkenguye, W., Njau, R., Kajoka, H., Santos, P. C. P., Shewiyo, E. J., Staton, C. A., Mmbaga, B. T., & Vissoci, J. R. N. (2026). The Challenges of Predicting Rare Outcomes: A Critical Appraisal of Machine Learning Using the Pediatric Resuscitation and Trauma Outcome (PRESTO) Model in a Tanzanian Injury Registry. World Journal of Surgery. https://doi.org/10.1002/wjs.70553
Source records
- crossref · retrieved 2026-09-26T08:51:32.342Z