Machine learning based on clinical characteristics and chest CT quantitative measurements for prediction of adverse clinical outcomes in hospitalized patients with COVID-19

OBJECTIVES: To develop and validate a machine learning model for the prediction of adverse outcomes in hospitalized patients with COVID-19. METHODS: We included 424 patients with non-severe COVID-19 on admission from January 17, 2020, to February 17, 2020, in the primary cohort of this retrospective...

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Detalles Bibliográficos
Autores principales: Feng, Zhichao, Shen, Hui, Gao, Kai, Su, Jianpo, Yao, Shanhu, Liu, Qin, Yan, Zhimin, Duan, Junhong, Yi, Dali, Zhao, Huafei, Li, Huiling, Yu, Qizhi, Zhou, Wenming, Mao, Xiaowen, Ouyang, Xin, Mei, Ji, Zeng, Qiuhua, Williams, Lindy, Ma, Xiaoqian, Rong, Pengfei, Hu, Dewen, Wang, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Imaging Informatics and Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8046645/
https://www.ncbi.nlm.nih.gov/pubmed/33856514
http://dx.doi.org/10.1007/s00330-021-07957-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8046645/
https://www.ncbi.nlm.nih.gov/pubmed/33856514
http://dx.doi.org/10.1007/s00330-021-07957-z

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