An explainable supervised machine learning predictor of acute kidney injury after adult deceased donor liver transplantation

An explainable supervised machine learning predictor of acute kidney injury after adult deceased donor liver transplantation

Abstract Background Early prediction of acute kidney injury (AKI) after liver transplantation (LT) facilitates timely recognition and intervention. We aimed to build a risk predictor of post-LT AKI via supervised machine learning and visualize the mechanism driving within to assist clinical decision...

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Bibliographic Details
Main Authors: Yihan Zhang, Dong Yang, Zifeng Liu, Chaojin Chen, Mian Ge, Xiang Li, Tongsen Luo, Zhengdong Wu, Chenguang Shi, Bohan Wang, Xiaoshuai Huang, Xiaodong Zhang, Shaoli Zhou, Ziqing Hei
Format: Article
Language:English
Published: BMC 2021-07-01
Series:Journal of Translational Medicine
Subjects:
Kidney dysfunction
Liver transplant
SHapley Additive exPlaination methods
SHAP value
Gradient boosting machine
Perioperative medicine
Online Access:https://doi.org/10.1186/s12967-021-02990-4

Internet

https://doi.org/10.1186/s12967-021-02990-4

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