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Predicting Missing Values in Medical Data Via XGBoost Regression

The data in a patient’s laboratory test result is a notable resource to support clinical investigation and enhance medical research. However, for a variety of reasons, this type of data often contains a non-trivial number of missing values. For example, physicians may neglect to order tests or docum...

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Detalhes bibliográficos
Publicado no:J Healthc Inform Res
Main Authors: Zhang, Xinmeng, Yan, Chao, Gao, Cheng, Malin, Bradley A., Chen, You
Formato: Artigo
Idioma:Inglês
Publicado em: Springer International Publishing 2020
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7709926/
https://ncbi.nlm.nih.gov/pubmed/33283143
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s41666-020-00077-1
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