Data heterogeneity and algorithmic bias in AI-based antimicrobial resistance prediction: a systematic review and mitigation framework.
- DOI
- 10.1186/s12911-026-03729-1
- Published
- 2026 Jul 29
- Container
- BMC medical informatics and decision making
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 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.
- 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.
- 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:10.1186/s12911-026-03729-1,
title = {Data heterogeneity and algorithmic bias in AI-based antimicrobial resistance prediction: a systematic review and mitigation framework.},
author = {Kiazolu J},
year = {2026},
journal = {BMC medical informatics and decision making},
doi = {10.1186/s12911-026-03729-1},
url = {https://doi.org/10.1186/s12911-026-03729-1}
}RIS
TY - JOUR TI - Data heterogeneity and algorithmic bias in AI-based antimicrobial resistance prediction: a systematic review and mitigation framework. AU - Kiazolu J PY - 2026 JO - BMC medical informatics and decision making DO - 10.1186/s12911-026-03729-1 UR - https://doi.org/10.1186/s12911-026-03729-1 ER -
APA
J, K. (2026). Data heterogeneity and algorithmic bias in AI-based antimicrobial resistance prediction: a systematic review and mitigation framework.. BMC medical informatics and decision making. https://doi.org/10.1186/s12911-026-03729-1
Source records
- pubmed · retrieved 2026-11-10T21:43:41.571Z