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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Опубликовано в: :PeerJ
Главные авторы: Lei, Lei, Wang, Ying, Xue, Qiong, Tong, Jianhua, Zhou, Cheng-Mao, Yang, Jian-Jun
Формат: Artigo
Язык:Inglês
Опубликовано: PeerJ Inc. 2020
Предметы:
Bioinformatics
Online-ссылка: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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