A descriptive study of random forest algorithm for predicting COVID-19 patients outcome

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) that occurred in Wuhan, China, has become a global public health threat. It is necessary to identify indicators that can be used as optimal predictors for clinical outcomes of COVID-19 patients. METHODS: The clinical information from 12...

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Detalles Bibliográficos
Autores principales: Wang, Jie, Yu, Heping, Hua, Qingquan, Jing, Shuili, Liu, Zhifen, Peng, Xiang, Cao, Cheng’an, Luo, Yongwen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Emergency and Critical Care
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7486830/
https://www.ncbi.nlm.nih.gov/pubmed/32974109
http://dx.doi.org/10.7717/peerj.9945

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7486830/
https://www.ncbi.nlm.nih.gov/pubmed/32974109
http://dx.doi.org/10.7717/peerj.9945

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