Application of explainable ensemble artificial intelligence model to categorization of hemodialysis-patient and treatment using nationwide-real-world data in Japan

BACKGROUND: Although dialysis patients are at a high risk of death, it is difficult for medical practitioners to simultaneously evaluate many inter-related risk factors. In this study, we evaluated the characteristics of hemodialysis patients using machine learning model, and its usefulness for scre...

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Detalhes bibliográficos
Publicado no:PLoS One
Main Authors: Kanda, Eiichiro, Epureanu, Bogdan I., Adachi, Taiji, Tsuruta, Yuki, Kikuchi, Kan, Kashihara, Naoki, Abe, Masanori, Masakane, Ikuto, Nitta, Kosaku
Formato: Artigo
Idioma:Inglês
Publicado em: Public Library of Science 2020
Assuntos:
Research Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7259704/
https://ncbi.nlm.nih.gov/pubmed/32469924
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0233491
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