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PSSPNN: PatchShuffle Stochastic Pooling Neural Network for an Explainable Diagnosis of COVID-19 with Multiple-Way Data Augmentation
AIM: COVID-19 has caused large death tolls all over the world. Accurate diagnosis is of significant importance for early treatment. METHODS: In this study, we proposed a novel PSSPNN model for classification between COVID-19, secondary pulmonary tuberculosis, community-captured pneumonia, and health...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Hindawi
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7945676/ https://www.ncbi.nlm.nih.gov/pubmed/33777167 http://dx.doi.org/10.1155/2021/6633755 |