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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...
Hauptverfasser: | , , , , , , |
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Format: | Online Artikel Text |
Sprache: | English |
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2021
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Online Zugang: | 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 |