Improved swin transformer-based thorax disease classification with optimal feature selection using chest X-ray.
Thoracic diseases, including pneumonia, tuberculosis, lung cancer, and others, pose significant health risks and require timely and accurate diagnosis to ensure proper treatment. Thus, in this research, a model for thorax disease classification using Chest X-rays is proposed by considering deep lear...
Saved in:
| Main Authors: | Nadim Rana, Yahaya Coulibaly, Ayman Noor, Talal H Noor, Md Imran Alam, Zeba Khan, Ali Tahir, Mohammad Zubair Khan |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0327099 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Improved swin transformer-based thorax disease classification with optimal feature selection using chest X-ray
by: Nadim Rana, et al.
Published: (2025-01-01) -
Turkish Chest X-Ray Report Generation Model Using the Swin Enhanced Yield Transformer (Model-SEY) Framework
by: Murat Ucan, et al.
Published: (2025-07-01) -
Application of Transformer Models for Classification of Chest X-rays
by: Enoel Arrokho Ernandes
Published: (2023-10-01) -
Stochastic-based learning for image classification in chest X-ray diagnosis
by: Xinghui Zeng, et al.
Published: (2025-08-01) -
Achieving Faster and Smarter Chest X-Ray Classification With Optimized CNNs
by: Hassen Louati, et al.
Published: (2025-01-01)