Improving diagnosis and interpretability in chest X-rays through federated learning and adversarial training
Abstract Background Chest X-ray imaging is the most common radiological test for diagnosing a wide range of lung conditions. Deep Learning (DL) has emerged as a powerful tool for automated analysis of chest X-rays, but it requires large, well-annotated datasets that are often difficult to obtain due to privacy concerns...
Carlos F. Del Cerro, Adri Gómez, Shadi Albarqouni et al.
· BMC Medical Informatics and... · 0 citations