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UncertaintyFuseNet: Robust uncertainty-aware hierarchical feature fusion model with Ensemble Monte Carlo Dropout for COVID-19 detection
The COVID-19 (Coronavirus disease 2019) pandemic has become a major global threat to human health and well-being. Thus, the development of computer-aided detection (CAD) systems that are capable of accurately distinguishing COVID-19 from other diseases using chest computed tomography (CT) and X-ray...
Autores principales: | Abdar, Moloud, Salari, Soorena, Qahremani, Sina, Lam, Hak-Keung, Karray, Fakhri, Hussain, Sadiq, Khosravi, Abbas, Acharya, U. Rajendra, Makarenkov, Vladimir, Nahavandi, Saeid |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9534540/ https://www.ncbi.nlm.nih.gov/pubmed/36217534 http://dx.doi.org/10.1016/j.inffus.2022.09.023 |
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