Deep learning attention-guided radiomics for COVID-19 chest radiograph classification

BACKGROUND: Accurate assessment of coronavirus disease 2019 (COVID-19) lung involvement through chest radiograph plays an important role in effective management of the infection. This study aims to develop a two-step feature merging method to integrate image features from deep learning and radiomics...

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Detalles Bibliográficos
Autores principales: Yang, Dongrong, Ren, Ge, Ni, Ruiyan, Huang, Yu-Hua, Lam, Ngo Fung Daniel, Sun, Hongfei, Wan, Shiu Bun Nelson, Wong, Man Fung Esther, Chan, King Kwong, Tsang, Hoi Ching Hailey, Xu, Lu, Wu, Tak Chiu, Kong, Feng-Ming (Spring), Wáng, Yì Xiáng J., Qin, Jing, Chan, Lawrence Wing Chi, Ying, Michael, Cai, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9929417/
https://www.ncbi.nlm.nih.gov/pubmed/36819269
http://dx.doi.org/10.21037/qims-22-531

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9929417/
https://www.ncbi.nlm.nih.gov/pubmed/36819269
http://dx.doi.org/10.21037/qims-22-531

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