An interpretable machine learning model based on a quick pre-screening system enables accurate deterioration risk prediction for COVID-19

An interpretable machine learning model based on a quick pre-screening system enables accurate deterioration risk prediction for COVID-19

Abstract A high-performing interpretable model is proposed to predict the risk of deterioration in coronavirus disease 2019 (COVID-19) patients. The model was developed using a cohort of 3028 patients diagnosed with COVID-19 and exhibiting common clinical symptoms that were internally verified (AUC...

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Autores principales: Lijing Jia, Zijian Wei, Heng Zhang, Jiaming Wang, Ruiqi Jia, Manhong Zhou, Xueyan Li, Hankun Zhang, Xuedong Chen, Zheyuan Yu, Zhaohong Wang, Xiucheng Li, Tingting Li, Xiangge Liu, Pei Liu, Wei Chen, Jing Li, Kunlun He
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Medicine
R
Science
Q
Acceso en línea:https://doaj.org/article/c181bf448c074d5eb8ad5f7c833512ad
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https://doaj.org/article/c181bf448c074d5eb8ad5f7c833512ad

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