Advancing early detection of chromophobe renal cell carcinoma: a Bayesian optimization approach to machine learning models.
- DOI
- 10.1038/s41598-026-46492-z
- Published
- 2026 Apr 8
- Container
- Scientific reports
- 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.
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-46492-z,
title = {Advancing early detection of chromophobe renal cell carcinoma: a Bayesian optimization approach to machine learning models.},
author = {Chen Y and Zhou Q and Hussain L and Wei Y and Wang J and Xia T},
year = {2026},
journal = {Scientific reports},
doi = {10.1038/s41598-026-46492-z},
url = {https://doi.org/10.1038/s41598-026-46492-z}
}RIS
TY - JOUR TI - Advancing early detection of chromophobe renal cell carcinoma: a Bayesian optimization approach to machine learning models. AU - Chen Y AU - Zhou Q AU - Hussain L AU - Wei Y AU - Wang J AU - Xia T PY - 2026 JO - Scientific reports DO - 10.1038/s41598-026-46492-z UR - https://doi.org/10.1038/s41598-026-46492-z ER -
APA
Y, C., Q, Z., L, H., Y, W., J, W., & T, X. (2026). Advancing early detection of chromophobe renal cell carcinoma: a Bayesian optimization approach to machine learning models.. Scientific reports. https://doi.org/10.1038/s41598-026-46492-z
Source records
- pubmed · retrieved 2026-09-26T00:01:55.077Z