A Deep Learning Radiomics Model to Identify Poor Outcome in COVID-19 Patients with Underlying Health Conditions: A Multicenter Study

Objective: Coronavirus disease 2019 (COVID-19) has caused considerable morbidity and mortality, especially in patients with underlying health conditions. A precise prognostic tool to identify poor outcomes among such cases is desperately needed. Methods: Total 400 COVID-19 patients with underlying h...

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Bibliographic Details
Main Authors:	Bai, Y. (Author), Dong, D. (Author), Hu, Y. (Author), Huang, Y. (Author), Li, H. (Author), Li, L. (Author), Liu, S. (Author), Lu, L. (Author), Qiu, X. (Author), Tian, J. (Author), Wang, M. (Author), Wang, S. (Author), Yu, X. (Author), Zha, Y. (Author)
Format:	Article
Language:	English
Published:	Institute of Electrical and Electronics Engineers Inc. 2021
Subjects:	3D modeling aged Aged Aged, 80 and over algorithm Article Bioinformatics bronchiectasis carcinoma cerebrovascular disease chronic kidney failure chronic liver disease chronic lung disease classifier clinical outcome clinical trial comorbidity Comorbidity computed tomography computer assisted diagnosis computer assisted tomography Computerized tomography Confidence interval controlled study coronavirus disease 2019 COVID-19 cross validation death deep learning Deep learning Deep Learning diabetes mellitus diagnostic imaging diagnostic test accuracy study feature extraction feature selection female Female follow up Health Health condition high risk patient hospital discharge hospitalization human Humans hypertension Imaging, Three-Dimensional Initial CT scan ischemic heart disease Learning systems low risk patient lung Lung lung volume major clinical study male Male middle aged Middle Aged Model performance morbidity mortality multicenter study Multicenter study pneumonia procedures prognosis Prognosis Radiographic Image Interpretation, Computer-Assisted radiomics real time reverse transcription polymerase chain reaction receiver operating characteristic Receiver operating characteristic curves Retrospective Studies retrospective study Risk assessment risk factor Risk stratification ROC Curve SARS-CoV-2 sensitivity and specificity survival analysis Survival analysis survival time three-dimensional imaging Tomography, X-Ray Computed training vasodilatation very elderly workflow x-ray computed tomography
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A Deep Learning Radiomics Model to Identify Poor Outcome in COVID-19 Patients with Underlying Health Conditions: A Multicenter Study

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