An explainable machine learning model for predicting postoperative cholangitis in pediatric surgical patients with pancreaticobiliary maljunction
- DOI
- 10.1186/s13040-025-00491-4
- Published
- 2025-11-19
- Container
- BioData Mining
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1186/s13040-025-00491-4,
title = {An explainable machine learning model for predicting postoperative cholangitis in pediatric surgical patients with pancreaticobiliary maljunction},
author = {Hui-min Mao and Jia Geng and Bin Zhu and Shun-gen Huang and Wan-liang Guo},
year = {2025},
journal = {BioData Mining},
doi = {10.1186/s13040-025-00491-4},
url = {https://doi.org/10.1186/s13040-025-00491-4}
}RIS
TY - JOUR TI - An explainable machine learning model for predicting postoperative cholangitis in pediatric surgical patients with pancreaticobiliary maljunction AU - Hui-min Mao AU - Jia Geng AU - Bin Zhu AU - Shun-gen Huang AU - Wan-liang Guo PY - 2025 JO - BioData Mining DO - 10.1186/s13040-025-00491-4 UR - https://doi.org/10.1186/s13040-025-00491-4 ER -
APA
Mao, H., Geng, J., Zhu, B., Huang, S., & Guo, W. (2025). An explainable machine learning model for predicting postoperative cholangitis in pediatric surgical patients with pancreaticobiliary maljunction. BioData Mining. https://doi.org/10.1186/s13040-025-00491-4
Source records
- crossref · retrieved 2026-09-26T06:01:15.260Z