Prediction Models for Periprosthetic Joint Infection: A Systematic Review of Traditional and Machine Learning Approaches.
- DOI
- 10.1016/j.mcpdig.2026.100392
- Published
- 2026 Dec
- Container
- Mayo Clinic proceedings. Digital health
- 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:10.1016/j.mcpdig.2026.100392,
title = {Prediction Models for Periprosthetic Joint Infection: A Systematic Review of Traditional and Machine Learning Approaches.},
author = {Pourghazi F and Alavi SMA and Borgonovo F and Petri F and Matsuo T and Abdel MP and Wyles CC and Gori A and Tande AJ and Berbari EF},
year = {2026},
journal = {Mayo Clinic proceedings. Digital health},
doi = {10.1016/j.mcpdig.2026.100392},
url = {https://doi.org/10.1016/j.mcpdig.2026.100392}
}RIS
TY - JOUR TI - Prediction Models for Periprosthetic Joint Infection: A Systematic Review of Traditional and Machine Learning Approaches. AU - Pourghazi F AU - Alavi SMA AU - Borgonovo F AU - Petri F AU - Matsuo T AU - Abdel MP AU - Wyles CC AU - Gori A AU - Tande AJ AU - Berbari EF PY - 2026 JO - Mayo Clinic proceedings. Digital health DO - 10.1016/j.mcpdig.2026.100392 UR - https://doi.org/10.1016/j.mcpdig.2026.100392 ER -
APA
F, P., SMA, A., F, B., F, P., T, M., MP, A., CC, W., A, G., AJ, T., & EF, B. (2026). Prediction Models for Periprosthetic Joint Infection: A Systematic Review of Traditional and Machine Learning Approaches.. Mayo Clinic proceedings. Digital health. https://doi.org/10.1016/j.mcpdig.2026.100392
Source records
- pubmed · retrieved 2026-09-26T05:18:13.232Z