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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2022
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Materias: | |
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 |
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