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The usage of deep neural network improves distinguishing COVID-19 from other suspected viral pneumonia by clinicians on chest CT: a real-world study
OBJECTIVES: Based on the current clinical routine, we aimed to develop a novel deep learning model to distinguish coronavirus disease 2019 (COVID-19) pneumonia from other types of pneumonia and validate it with a real-world dataset (RWD). METHODS: A total of 563 chest CT scans of 380 patients (227/3...
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| Pubblicato in: | Eur Radiol |
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| Autori principali: | , , , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Springer Berlin Heidelberg
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7769567/ https://ncbi.nlm.nih.gov/pubmed/33372243 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00330-020-07553-7 |
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