Clinically-aligned explainable AI for atrial fibrillation detection: A U-Net inspired multi-lead ECG analysis framework.
- DOI
- 10.1016/j.cmpb.2026.109474
- Published
- 2026 Oct
- Container
- Computer methods and programs in biomedicine
- 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:10.1016/j.cmpb.2026.109474,
title = {Clinically-aligned explainable AI for atrial fibrillation detection: A U-Net inspired multi-lead ECG analysis framework.},
author = {Taleban A and Sparapani R and Zlochiver S and Lu Q and Widlansky ME and Luo J},
year = {2026},
journal = {Computer methods and programs in biomedicine},
doi = {10.1016/j.cmpb.2026.109474},
url = {https://doi.org/10.1016/j.cmpb.2026.109474}
}RIS
TY - JOUR TI - Clinically-aligned explainable AI for atrial fibrillation detection: A U-Net inspired multi-lead ECG analysis framework. AU - Taleban A AU - Sparapani R AU - Zlochiver S AU - Lu Q AU - Widlansky ME AU - Luo J PY - 2026 JO - Computer methods and programs in biomedicine DO - 10.1016/j.cmpb.2026.109474 UR - https://doi.org/10.1016/j.cmpb.2026.109474 ER -
APA
A, T., R, S., S, Z., Q, L., ME, W., & J, L. (2026). Clinically-aligned explainable AI for atrial fibrillation detection: A U-Net inspired multi-lead ECG analysis framework.. Computer methods and programs in biomedicine. https://doi.org/10.1016/j.cmpb.2026.109474
Source records
- pubmed · retrieved 2026-09-24T19:52:07.148Z