A comparative study of machine learning algorithms for predicting acute kidney injury after liver cancer resection

OBJECTIVE: Machine learning methods may have better or comparable predictive ability than traditional analysis. We explore machine learning methods to predict the likelihood of acute kidney injury after liver cancer resection. METHODS: This is a secondary analysis cohort study. We reviewed data from...

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Detalles Bibliográficos
Publicado en:PeerJ
Main Authors: Lei, Lei, Wang, Ying, Xue, Qiong, Tong, Jianhua, Zhou, Cheng-Mao, Yang, Jian-Jun
Formato: Artigo
Idioma:Inglês
Publicado: PeerJ Inc. 2020
Assuntos:
Bioinformatics
Acceso en liña:https://ncbi.nlm.nih.gov/pmc/articles/PMC7047869/
https://ncbi.nlm.nih.gov/pubmed/32140301
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.7717/peerj.8583
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