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

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-making....

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Detalles Bibliográficos
Autores principales: Zhang, Yihan, Yang, Dong, Liu, Zifeng, Chen, Chaojin, Ge, Mian, Li, Xiang, Luo, Tongsen, Wu, Zhengdong, Shi, Chenguang, Wang, Bohan, Huang, Xiaoshuai, Zhang, Xiaodong, Zhou, Shaoli, Hei, Ziqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8317304/
https://www.ncbi.nlm.nih.gov/pubmed/34321016
http://dx.doi.org/10.1186/s12967-021-02990-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8317304/
https://www.ncbi.nlm.nih.gov/pubmed/34321016
http://dx.doi.org/10.1186/s12967-021-02990-4

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