Cargando…
Deep learning-based analysis of COVID-19 X-ray images: Incorporating clinical significance and assessing misinterpretation
COVID-19, pneumonia, and tuberculosis have had a significant effect on recent global health. Since 2019, COVID-19 has been a major factor underlying the increase in respiratory-related terminal illness. Early-stage interpretation and identification of these diseases from X-ray images is essential to...
Autores principales: | Islam Bhuiyan, Md. Rahad, Azam, Sami, Montaha, Sidratul, Jim, Risul Islam, Karim, Asif, Khan, Inam Ullah, Brady, Mark, Hasan, Md. Zahid, De Boer, Friso, Mukta, Md. Saddam Hossain |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668574/ https://www.ncbi.nlm.nih.gov/pubmed/38025114 http://dx.doi.org/10.1177/20552076231215915 |
Ejemplares similares
-
Automated breast tumor ultrasound image segmentation with hybrid UNet and classification using fine-tuned CNN model
por: Hossain, Shahed, et al.
Publicado: (2023) -
BreastNet18: A High Accuracy Fine-Tuned VGG16 Model Evaluated Using Ablation Study for Diagnosing Breast Cancer from Enhanced Mammography Images
por: Montaha, Sidratul, et al.
Publicado: (2021) -
Automated Detection of Broncho-Arterial Pairs Using CT Scans Employing Different Approaches to Classify Lung Diseases
por: Azam, Sami, et al.
Publicado: (2023) -
An Effective Ensemble Machine Learning Approach to Classify Breast Cancer Based on Feature Selection and Lesion Segmentation Using Preprocessed Mammograms
por: Rafid, A. K. M. Rakibul Haque, et al.
Publicado: (2022) -
Development of an automated optimal distance feature-based decision system for diagnosing knee osteoarthritis using segmented X-ray images
por: Fatema, Kaniz, et al.
Publicado: (2023)