Interpretable machine learning for cardiovascular disease risk prediction in cancer survivors: development and internal validation.
- DOI
- 10.1186/s40959-026-00547-2
- Published
- 2026 Jul 20
- Container
- Cardio-oncology (London, England)
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1186/s40959-026-00547-2,
title = {Interpretable machine learning for cardiovascular disease risk prediction in cancer survivors: development and internal validation.},
author = {Zhang G and Zhang X and Jia C and Zhou H and Sun X and Liu H},
year = {2026},
journal = {Cardio-oncology (London, England)},
doi = {10.1186/s40959-026-00547-2},
url = {https://doi.org/10.1186/s40959-026-00547-2}
}RIS
TY - JOUR TI - Interpretable machine learning for cardiovascular disease risk prediction in cancer survivors: development and internal validation. AU - Zhang G AU - Zhang X AU - Jia C AU - Zhou H AU - Sun X AU - Liu H PY - 2026 JO - Cardio-oncology (London, England) DO - 10.1186/s40959-026-00547-2 UR - https://doi.org/10.1186/s40959-026-00547-2 ER -
APA
G, Z., X, Z., C, J., H, Z., X, S., & H, L. (2026). Interpretable machine learning for cardiovascular disease risk prediction in cancer survivors: development and internal validation.. Cardio-oncology (London, England). https://doi.org/10.1186/s40959-026-00547-2
Source records
- pubmed · retrieved 2026-09-26T19:13:40.011Z