Multiparametric MRI-Based Interpretable Machine Learning Radiomics Model for Predicting Neoadjuvant Chemotherapy Sensitivity and Recurrence-Free Survival in Breast Cancer.
- DOI
- 10.1016/j.acra.2026.07.065
- Published
- 2026 Aug 26
- Container
- Academic radiology
- Publisher
- Not recorded
- Open access
- unknown
Credibility signals
limited evidence Score 43/100 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.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- 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.acra.2026.07.065,
title = {Multiparametric MRI-Based Interpretable Machine Learning Radiomics Model for Predicting Neoadjuvant Chemotherapy Sensitivity and Recurrence-Free Survival in Breast Cancer.},
author = {Zeng X and Zeng X and Tang X and Xiao J and Peng J},
year = {2026},
journal = {Academic radiology},
doi = {10.1016/j.acra.2026.07.065},
url = {https://doi.org/10.1016/j.acra.2026.07.065}
}RIS
TY - JOUR TI - Multiparametric MRI-Based Interpretable Machine Learning Radiomics Model for Predicting Neoadjuvant Chemotherapy Sensitivity and Recurrence-Free Survival in Breast Cancer. AU - Zeng X AU - Zeng X AU - Tang X AU - Xiao J AU - Peng J PY - 2026 JO - Academic radiology DO - 10.1016/j.acra.2026.07.065 UR - https://doi.org/10.1016/j.acra.2026.07.065 ER -
APA
X, Z., X, Z., X, T., J, X., & J, P. (2026). Multiparametric MRI-Based Interpretable Machine Learning Radiomics Model for Predicting Neoadjuvant Chemotherapy Sensitivity and Recurrence-Free Survival in Breast Cancer.. Academic radiology. https://doi.org/10.1016/j.acra.2026.07.065
Source records
- pubmed · retrieved 2026-09-25T07:44:37.760Z