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    An Explainable Machine Learning Model to Predict Acute Kidney Injury After Cardiac Surgery: A Retrospective Cohort Study by Gao Y, Wang C, Dong W, Li B, Wang J, Li J, Tian Y, Liu J, Wang Y

    Published 2023-12-01
    “…Yuchen Gao,1,* Chunrong Wang,2,* Wenhao Dong,3 Bianfang Li,3 Jianhui Wang,1 Jun Li,1 Yu Tian,1 Jia Liu,1 Yuefu Wang3 1Department of Anesthesiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China; 2Department of Anesthesiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China; 3Department of Surgical Intensive Care Unit & Anesthesiology, Beijing Shijitan Hospital, Capital Medical University, Beijing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yuefu Wang, Department of Surgical Intensive Care Unit & Anesthesiology, Beijing Shijitan Hospital, Capital Medical University, 10 Tieyi Road, Haidian District, Beijing, People’s Republic of China, Email wangyuefu3806@bjsjth.cnBackground: To derive and validate a machine learning (ML) prediction model of acute kidney injury (AKI) that could be used for AKI surveillance and management to improve clinical outcomes.Methods: This retrospective cohort study was conducted in Fuwai Hospital, including patients aged 18 years and above undergoing cardiac surgery admitted between January 1, 2017, and December 31, 2018. …”
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