Artificial intelligence and image processing framework for automated airway invasion detection and residue classification from swallowing endoscopy.
- DOI
- 10.1038/s41598-026-44495-4
- Published
- 2026 Apr 10
- 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/s41598-026-44495-4,
title = {Artificial intelligence and image processing framework for automated airway invasion detection and residue classification from swallowing endoscopy.},
author = {Araújo L and Rangel E and Cotrina-Atencio A and Dos Santos VG and da Costa Dos Santos Reis AM and Magalhães H and Ferreira L and de Azevedo Dantas AFO and do Espírito-Santo CC},
year = {2026},
journal = {Scientific reports},
doi = {10.1038/s41598-026-44495-4},
url = {https://doi.org/10.1038/s41598-026-44495-4}
}RIS
TY - JOUR TI - Artificial intelligence and image processing framework for automated airway invasion detection and residue classification from swallowing endoscopy. AU - Araújo L AU - Rangel E AU - Cotrina-Atencio A AU - Dos Santos VG AU - da Costa Dos Santos Reis AM AU - Magalhães H AU - Ferreira L AU - de Azevedo Dantas AFO AU - do Espírito-Santo CC PY - 2026 JO - Scientific reports DO - 10.1038/s41598-026-44495-4 UR - https://doi.org/10.1038/s41598-026-44495-4 ER -
APA
L, A., E, R., A, C., VG, D. S., AM, D. C. D. S. R., H, M., L, F., AFO, D. A. D., & CC, D. E. (2026). Artificial intelligence and image processing framework for automated airway invasion detection and residue classification from swallowing endoscopy.. Scientific reports. https://doi.org/10.1038/s41598-026-44495-4
Source records
- pubmed · retrieved 2026-09-27T06:44:39.854Z