Dual context attentive feature network: an interpretable dual-pathway deep learning framework for accurate gastrointestinal endoscopic image classification

Omar AlOmair, Zohaib Khurshid

Open source

DOI: 10.21037/qims-2026-1389
Published: 2026-11
Container: Quantitative Imaging in Medicine and Surgery
Publisher: AME Publishing Company
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. Source: Crossref; license: CC0 metadata
supportingDOI resolves: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
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. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.21037/qims-2026-1389,
  title = {Dual context attentive feature network: an interpretable dual-pathway deep learning framework for accurate gastrointestinal endoscopic image classification},
  author = {Omar AlOmair and Zohaib Khurshid},
  year = {2026},
  journal = {Quantitative Imaging in Medicine and Surgery},
  doi = {10.21037/qims-2026-1389},
  url = {https://doi.org/10.21037/qims-2026-1389}
}

RIS

TY  - JOUR
TI  - Dual context attentive feature network: an interpretable dual-pathway deep learning framework for accurate gastrointestinal endoscopic image classification
AU  - Omar AlOmair
AU  - Zohaib Khurshid
PY  - 2026
JO  - Quantitative Imaging in Medicine and Surgery
DO  - 10.21037/qims-2026-1389
UR  - https://doi.org/10.21037/qims-2026-1389
ER  -

APA

AlOmair, O., & Khurshid, Z. (2026). Dual context attentive feature network: an interpretable dual-pathway deep learning framework for accurate gastrointestinal endoscopic image classification. Quantitative Imaging in Medicine and Surgery. https://doi.org/10.21037/qims-2026-1389

Source records

crossref · retrieved 2026-11-10T02:01:33.949Z