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Prediction of Acute Kidney Injury After Cardiac Surgery Using Interpretable Machine Learning
17
Zitationen
11
Autoren
2022
Jahr
Abstract
The treatment team can be informed about the possibility of postoperative AKI before cardiac surgery using machine learning models such as RF and XGBoost and adjust the treatment procedure accordingly. Interpretability of predictions for each patient ensures the validity of obtained predictions.
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