Development and validation of a machine learning clinicogenomic model to improve prognostic stratification in ER-positive/HER2-negative early breast cancer
- DOI
- 10.1186/s13058-026-02388-4
- Published
- 2026-09-16
- Container
- Breast Cancer Research
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1186/s13058-026-02388-4,
title = {Development and validation of a machine learning clinicogenomic model to improve prognostic stratification in ER-positive/HER2-negative early breast cancer},
author = {Michail Sarafidis and Emmanouil G. Sifakis and Jonas Bergh and Theodoros Foukakis and Alexios Matikas},
year = {2026},
journal = {Breast Cancer Research},
doi = {10.1186/s13058-026-02388-4},
url = {https://doi.org/10.1186/s13058-026-02388-4}
}RIS
TY - JOUR TI - Development and validation of a machine learning clinicogenomic model to improve prognostic stratification in ER-positive/HER2-negative early breast cancer AU - Michail Sarafidis AU - Emmanouil G. Sifakis AU - Jonas Bergh AU - Theodoros Foukakis AU - Alexios Matikas PY - 2026 JO - Breast Cancer Research DO - 10.1186/s13058-026-02388-4 UR - https://doi.org/10.1186/s13058-026-02388-4 ER -
APA
Sarafidis, M., Sifakis, E. G., Bergh, J., Foukakis, T., & Matikas, A. (2026). Development and validation of a machine learning clinicogenomic model to improve prognostic stratification in ER-positive/HER2-negative early breast cancer. Breast Cancer Research. https://doi.org/10.1186/s13058-026-02388-4
Source records
- crossref · retrieved 2026-11-11T01:26:15.331Z