Cargando…
Dynamic learning for imbalanced data in learning chest X-ray and CT images
Massive annotated datasets are necessary for networks of deep learning. When a topic is being researched for the first time, as in the situation of the viral epidemic, handling it with limited annotated datasets might be difficult. Additionally, the datasets are quite unbalanced in this situation, w...
Autores principales: | Iqbal, Saeed, Qureshi, Adnan N., Li, Jianqiang, Choudhry, Imran Arshad, Mahmood, Tariq |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10258426/ https://www.ncbi.nlm.nih.gov/pubmed/37313141 http://dx.doi.org/10.1016/j.heliyon.2023.e16807 |
Ejemplares similares
-
Learning from imbalanced COVID-19 chest X-ray (CXR) medical imaging data
por: Chan, Jonathan H., et al.
Publicado: (2022) -
On the Analyses of Medical Images Using Traditional Machine Learning Techniques and Convolutional Neural Networks
por: Iqbal, Saeed, et al.
Publicado: (2023) -
How intra-source imbalanced datasets impact the performance of deep learning for COVID-19 diagnosis using chest X-ray images
por: Zhang, Zhang, et al.
Publicado: (2023) -
Variational Autoencoder Based Imbalanced COVID-19 Detection Using Chest X-Ray Images
por: Chatterjee, Sankhadeep, et al.
Publicado: (2022) -
Deep Learning-Based Classification of Chest Diseases Using X-rays, CT Scans, and Cough Sound Images
por: Malik, Hassaan, et al.
Publicado: (2023)