Machine learning approaches for predicting breast cancer recurrence using clinical and histopathological data
- DOI
- 10.1007/s10238-025-02018-x
- Published
- 2025-12-30
- Container
- Clinical and Experimental Medicine
- Publisher
- Springer Science and Business Media LLC
- 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.
- supportingDOI resolves: A matching record was returned by Crossref.
- 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.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1007/s10238-025-02018-x,
title = {Machine learning approaches for predicting breast cancer recurrence using clinical and histopathological data},
author = {Mohd Abas Bhat and Mushtaq Ahmad Mir and R. Vijaya Lakshmi and Tejaswini Pradhan and G. V. V. Jagannadha Rao and Ghanshyam G. Tejani and Syed Abid Hussain},
year = {2025},
journal = {Clinical and Experimental Medicine},
doi = {10.1007/s10238-025-02018-x},
url = {https://doi.org/10.1007/s10238-025-02018-x}
}RIS
TY - JOUR TI - Machine learning approaches for predicting breast cancer recurrence using clinical and histopathological data AU - Mohd Abas Bhat AU - Mushtaq Ahmad Mir AU - R. Vijaya Lakshmi AU - Tejaswini Pradhan AU - G. V. V. Jagannadha Rao AU - Ghanshyam G. Tejani AU - Syed Abid Hussain PY - 2025 JO - Clinical and Experimental Medicine DO - 10.1007/s10238-025-02018-x UR - https://doi.org/10.1007/s10238-025-02018-x ER -
APA
Bhat, M. A., Mir, M. A., Lakshmi, R. V., Pradhan, T., Rao, G. V. V. J., Tejani, G. G., & Hussain, S. A. (2025). Machine learning approaches for predicting breast cancer recurrence using clinical and histopathological data. Clinical and Experimental Medicine. https://doi.org/10.1007/s10238-025-02018-x
Source records
- crossref · retrieved 2026-11-03T13:53:13.839Z