HyRA-CXR: a hybrid residual–attention deep network for chest X-ray classification
Wadhah Zeyad Tareq
Chest X-ray (CXR) interpretation is essential for diagnosing pulmonary diseases, yet manual reading remains slow and prone to human error, especially in high-volume or resource-limited settings. To address delayed diagnoses and improve clinical efficiency, this study introduces (HyRA-CXR), a hybrid residual–attention convolutional neural network for automated CXR classification. The proposed model integrates residual blocks to enhance gradient stability and dual attention mechanisms to focus on