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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...
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| Publicado no: | Int J Gen Med |
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| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Dove
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8057825/ https://ncbi.nlm.nih.gov/pubmed/33889012 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.2147/IJGM.S302795 |
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