Machine Learning-Based Prediction of COVID-19 Severity and Progression to Critical Illness Using CT Imaging and Clinical Data

OBJECTIVE: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. MATERIALS AND METHODS: Clinical data were collected from 981 patients from a multi-insti...

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Detalles Bibliográficos
Autores principales: Purkayastha, Subhanik, Xiao, Yanhe, Jiao, Zhicheng, Thepumnoeysuk, Rujapa, Halsey, Kasey, Wu, Jing, Tran, Thi My Linh, Hsieh, Ben, Choi, Ji Whae, Wang, Dongcui, Vallières, Martin, Wang, Robin, Collins, Scott, Feng, Xue, Feldman, Michael, Zhang, Paul J., Atalay, Michael, Sebro, Ronnie, Yang, Li, Fan, Yong, Liao, Wei-hua, Bai, Harrison X.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Radiology 2021
Materias:
Thoracic Imaging
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236359/
https://www.ncbi.nlm.nih.gov/pubmed/33739635
http://dx.doi.org/10.3348/kjr.2020.1104

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236359/
https://www.ncbi.nlm.nih.gov/pubmed/33739635
http://dx.doi.org/10.3348/kjr.2020.1104

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