Evaluation of machine learning models for early prediction of gestational diabetes using retrospective electronic health records from current and previous pregnancies
- DOI
- 10.1136/bmjdhai-2025-000089
- Published
- 2025-12
- Container
- BMJ Digital Health & AI
- Publisher
- BMJ
- 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:10.1136/bmjdhai-2025-000089,
title = {Evaluation of machine learning models for early prediction of gestational diabetes using retrospective electronic health records from current and previous pregnancies},
author = {Mark Germaine and Amy C O’Higgins and Brendan Egan and Graham Healy},
year = {2025},
journal = {BMJ Digital Health \& AI},
doi = {10.1136/bmjdhai-2025-000089},
url = {https://doi.org/10.1136/bmjdhai-2025-000089}
}RIS
TY - JOUR TI - Evaluation of machine learning models for early prediction of gestational diabetes using retrospective electronic health records from current and previous pregnancies AU - Mark Germaine AU - Amy C O’Higgins AU - Brendan Egan AU - Graham Healy PY - 2025 JO - BMJ Digital Health & AI DO - 10.1136/bmjdhai-2025-000089 UR - https://doi.org/10.1136/bmjdhai-2025-000089 ER -
APA
Germaine, M., O’Higgins, A. C., Egan, B., & Healy, G. (2025). Evaluation of machine learning models for early prediction of gestational diabetes using retrospective electronic health records from current and previous pregnancies. BMJ Digital Health & AI. https://doi.org/10.1136/bmjdhai-2025-000089
Source records
- crossref · retrieved 2026-09-27T08:21:22.866Z