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Comparison of Prediction Models for Acute Kidney Injury Among Patients with Hepatobiliary Malignancies Based on XGBoost and LASSO-Logistic Algorithms
BACKGROUND: Based on the admission data, we applied the XGBoost algorithm to create a prediction model to estimate the AKI risk in patients with hepatobiliary malignancies and then compare its prediction capacity with the logistic model. METHODS: We reviewed clinical data of 7968 and 589 liver/gallb...
Autores principales: | , , , , , , |
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格式: | Online 文件 Texto |
语言: | English |
出版: |
Dove
2021
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主题: | |
在线阅读: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8057825/ https://www.ncbi.nlm.nih.gov/pubmed/33889012 http://dx.doi.org/10.2147/IJGM.S302795 |