Retinal features as predictive indicators for high myopia: insights from explainable multi-machine learning models
- DOI
- 10.3389/fbioe.2025.1609639
- Published
- 2025-10-13
- Container
- Frontiers in Bioengineering and Biotechnology
- Publisher
- Frontiers Media SA
- 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:10.3389/fbioe.2025.1609639,
title = {Retinal features as predictive indicators for high myopia: insights from explainable multi-machine learning models},
author = {Haohan Zou and Jing Liu and Shenda Shi and Saiguang Ling and Qian Fan and Yan Huo and Zhou Dong and Guoge Han and Shengjin Wang and Yan Wang},
year = {2025},
journal = {Frontiers in Bioengineering and Biotechnology},
doi = {10.3389/fbioe.2025.1609639},
url = {https://doi.org/10.3389/fbioe.2025.1609639}
}RIS
TY - JOUR TI - Retinal features as predictive indicators for high myopia: insights from explainable multi-machine learning models AU - Haohan Zou AU - Jing Liu AU - Shenda Shi AU - Saiguang Ling AU - Qian Fan AU - Yan Huo AU - Zhou Dong AU - Guoge Han AU - Shengjin Wang AU - Yan Wang PY - 2025 JO - Frontiers in Bioengineering and Biotechnology DO - 10.3389/fbioe.2025.1609639 UR - https://doi.org/10.3389/fbioe.2025.1609639 ER -
APA
Zou, H., Liu, J., Shi, S., Ling, S., Fan, Q., Huo, Y., Dong, Z., Han, G., Wang, S., & Wang, Y. (2025). Retinal features as predictive indicators for high myopia: insights from explainable multi-machine learning models. Frontiers in Bioengineering and Biotechnology. https://doi.org/10.3389/fbioe.2025.1609639
Source records
- crossref · retrieved 2026-09-25T23:48:19.876Z