A deep learning approach for keratoconus detection using spatio-temporal features from corneal imaging.
- DOI
- 10.1038/s41598-026-56383-y
- Published
- 2026 Jun 1
- Container
- Scientific reports
- 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:10.1038/s41598-026-56383-y,
title = {A deep learning approach for keratoconus detection using spatio-temporal features from corneal imaging.},
author = {Syta A and Chorągiewicz T and Gęca J and Karpiński R and Wróbel-Dudzińska D and Podkowiński A and Maciejewski M and Głuchowski D and Jonak KE and Rejdak R and Jonak K},
year = {2026},
journal = {Scientific reports},
doi = {10.1038/s41598-026-56383-y},
url = {https://doi.org/10.1038/s41598-026-56383-y}
}RIS
TY - JOUR TI - A deep learning approach for keratoconus detection using spatio-temporal features from corneal imaging. AU - Syta A AU - Chorągiewicz T AU - Gęca J AU - Karpiński R AU - Wróbel-Dudzińska D AU - Podkowiński A AU - Maciejewski M AU - Głuchowski D AU - Jonak KE AU - Rejdak R AU - Jonak K PY - 2026 JO - Scientific reports DO - 10.1038/s41598-026-56383-y UR - https://doi.org/10.1038/s41598-026-56383-y ER -
APA
A, S., T, C., J, G., R, K., D, W., A, P., M, M., D, G., KE, J., R, R., & K, J. (2026). A deep learning approach for keratoconus detection using spatio-temporal features from corneal imaging.. Scientific reports. https://doi.org/10.1038/s41598-026-56383-y
Source records
- pubmed · retrieved 2026-09-26T07:58:33.987Z