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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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| Опубликовано в: : | Radiol Cardiothorac Imaging |
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| Главные авторы: | , , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Radiological Society of North America
2021
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| Предметы: | |
| Online-ссылка: | 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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