Cargando…
Bayesian-based optimized deep learning model to detect COVID-19 patients using chest X-ray image data
Coronavirus Disease 2019 (COVID-19) is extremely infectious and rapidly spreading around the globe. As a result, rapid and precise identification of COVID-19 patients is critical. Deep Learning has shown promising performance in a variety of domains and emerged as a key technology in Artificial Inte...
Autores principales: | Loey, Mohamed, El-Sappagh, Shaker, Mirjalili, Seyedali |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8730711/ https://www.ncbi.nlm.nih.gov/pubmed/35026573 http://dx.doi.org/10.1016/j.compbiomed.2022.105213 |
Ejemplares similares
-
COVID-19 cough sound symptoms classification from scalogram image representation using deep learning models
por: Loey, Mohamed, et al.
Publicado: (2021) -
A comprehensive survey of recent trends in deep learning for digital images augmentation
por: Khalifa, Nour Eldeen, et al.
Publicado: (2021) -
A deep learning based dual encoder–decoder framework for anatomical structure segmentation in chest X-ray images
por: Ullah, Ihsan, et al.
Publicado: (2023) -
Diagnosis of COVID-19 Using Chest X-ray Images and Disease Symptoms Based on Stacking Ensemble Deep Learning
por: AlMohimeed, Abdulaziz, et al.
Publicado: (2023) -
Author Correction: A deep learning based dual encoder–decoder framework for anatomical structure segmentation in chest X-ray images
por: Ullah, Ihsan, et al.
Publicado: (2023)