Explainable machine learning for breast mass characterization and malignancy risk stratification: multimodal integration of AI-derived structured digital breast tomosynthesis features and peripheral blood immune-inflammatory biomarkers.
- DOI
- 10.3389/fcell.2026.1917987
- Published
- 2026
- Container
- Frontiers in cell and developmental biology
- 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:10.3389/fcell.2026.1917987,
title = {Explainable machine learning for breast mass characterization and malignancy risk stratification: multimodal integration of AI-derived structured digital breast tomosynthesis features and peripheral blood immune-inflammatory biomarkers.},
author = {Nie L and Wei Y and Feng X and Lu Y},
year = {2026},
journal = {Frontiers in cell and developmental biology},
doi = {10.3389/fcell.2026.1917987},
url = {https://doi.org/10.3389/fcell.2026.1917987}
}RIS
TY - JOUR TI - Explainable machine learning for breast mass characterization and malignancy risk stratification: multimodal integration of AI-derived structured digital breast tomosynthesis features and peripheral blood immune-inflammatory biomarkers. AU - Nie L AU - Wei Y AU - Feng X AU - Lu Y PY - 2026 JO - Frontiers in cell and developmental biology DO - 10.3389/fcell.2026.1917987 UR - https://doi.org/10.3389/fcell.2026.1917987 ER -
APA
L, N., Y, W., X, F., & Y, L. (2026). Explainable machine learning for breast mass characterization and malignancy risk stratification: multimodal integration of AI-derived structured digital breast tomosynthesis features and peripheral blood immune-inflammatory biomarkers.. Frontiers in cell and developmental biology. https://doi.org/10.3389/fcell.2026.1917987
Source records
- pubmed · retrieved 2026-09-25T03:51:45.286Z