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Deep Learning to Quantify Pulmonary Edema in Chest Radiographs
PURPOSE: To develop a machine learning model to classify the severity grades of pulmonary edema on chest radiographs. MATERIALS AND METHODS: In this retrospective study, 369 071 chest radiographs and associated radiology reports from 64 581 patients (mean age, 51.71 years; 54.51% women) from the MIM...
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| Publicado en: | Radiol Artif Intell |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
Radiological Society of North America
2021
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8043362/ https://ncbi.nlm.nih.gov/pubmed/33937857 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1148/ryai.2021190228 |
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