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...

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Detalles Bibliográficos
Autores principales: Wang, Shui-Hua, Zhang, Yin, Cheng, Xiaochun, Zhang, Xin, Zhang, Yu-Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Research Article
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

Internet

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

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