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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Bibliografiska uppgifter
I publikationen:Korean J Radiol
Huvudupphovsmän: 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.
Materialtyp: Artigo
Språk:Inglês
Publicerad: The Korean Society of Radiology 2021
Ämnen:
Thoracic Imaging
Länkar:https://ncbi.nlm.nih.gov/pmc/articles/PMC8236359/
https://ncbi.nlm.nih.gov/pubmed/33739635
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3348/kjr.2020.1104
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