Automated CT Staging of Chronic Obstructive Pulmonary Disease Severity for Predicting Disease Progression and Mortality with a Deep Learning Convolutional Neural Network

PURPOSE: To develop a deep learning–based algorithm to stage the severity of chronic obstructive pulmonary disease (COPD) through quantification of emphysema and air trapping on CT images and to assess the ability of the proposed stages to prognosticate 5-year progression and mortality. MATERIALS AN...

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Detalhes bibliográficos
Publicado no:Radiol Cardiothorac Imaging
Main Authors: Hasenstab, Kyle A., Yuan, Nancy, Retson, Tara, Conrad, Douglas J., Kligerman, Seth, Lynch, David A., Hsiao, Albert
Formato: Artigo
Idioma:Inglês
Publicado em: Radiological Society of North America 2021
Assuntos:
Original Research
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC8098086/
https://ncbi.nlm.nih.gov/pubmed/33969307
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1148/ryct.2021200477
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