MRICombo: a deep-learning-based framework for universal volumetric segmentation grading-staging and malignancy detection across heterogeneous MRI.
- DOI
- 10.1038/s41467-026-76461-z
- Published
- 2026 Aug 8
- Container
- Nature communications
- 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/s41467-026-76461-z,
title = {MRICombo: a deep-learning-based framework for universal volumetric segmentation grading-staging and malignancy detection across heterogeneous MRI.},
author = {Zhang Z and Han L and Jia D and Wei Y and Zhang T and Huang J and Huang D and Wang Y and Wu S and Kallenberg M and Mann R and Yan C and Sun Y and Tan T},
year = {2026},
journal = {Nature communications},
doi = {10.1038/s41467-026-76461-z},
url = {https://doi.org/10.1038/s41467-026-76461-z}
}RIS
TY - JOUR TI - MRICombo: a deep-learning-based framework for universal volumetric segmentation grading-staging and malignancy detection across heterogeneous MRI. AU - Zhang Z AU - Han L AU - Jia D AU - Wei Y AU - Zhang T AU - Huang J AU - Huang D AU - Wang Y AU - Wu S AU - Kallenberg M AU - Mann R AU - Yan C AU - Sun Y AU - Tan T PY - 2026 JO - Nature communications DO - 10.1038/s41467-026-76461-z UR - https://doi.org/10.1038/s41467-026-76461-z ER -
APA
Z, Z., L, H., D, J., Y, W., T, Z., J, H., D, H., Y, W., S, W., M, K., R, M., C, Y., Y, S., & T, T. (2026). MRICombo: a deep-learning-based framework for universal volumetric segmentation grading-staging and malignancy detection across heterogeneous MRI.. Nature communications. https://doi.org/10.1038/s41467-026-76461-z
Source records
- pubmed · retrieved 2026-09-26T08:57:32.851Z