Creation and verification of an interpretable machine learning model for forecasting in-hospital results in Cardiorenal syndrome patients in critical condition
- DOI
- 10.1080/14737159.2026.2760899
- Published
- 2026-11-05
- Container
- Expert Review of Molecular Diagnostics
- Publisher
- Informa UK Limited
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1080/14737159.2026.2760899,
title = {Creation and verification of an interpretable machine learning model for forecasting in-hospital results in Cardiorenal syndrome patients in critical condition},
author = {Zuoxun Xia and Ziying Peng and Peng Xu},
year = {2026},
journal = {Expert Review of Molecular Diagnostics},
doi = {10.1080/14737159.2026.2760899},
url = {https://doi.org/10.1080/14737159.2026.2760899}
}RIS
TY - JOUR TI - Creation and verification of an interpretable machine learning model for forecasting in-hospital results in Cardiorenal syndrome patients in critical condition AU - Zuoxun Xia AU - Ziying Peng AU - Peng Xu PY - 2026 JO - Expert Review of Molecular Diagnostics DO - 10.1080/14737159.2026.2760899 UR - https://doi.org/10.1080/14737159.2026.2760899 ER -
APA
Xia, Z., Peng, Z., & Xu, P. (2026). Creation and verification of an interpretable machine learning model for forecasting in-hospital results in Cardiorenal syndrome patients in critical condition. Expert Review of Molecular Diagnostics. https://doi.org/10.1080/14737159.2026.2760899
Source records
- crossref · retrieved 2026-11-06T23:29:36.322Z