Detecting Multi Thoracic Diseases in Chest X-Ray Images Using Deep Learning Techniques

This doctoral proposal introduces a novel method for detecting and diagnosing various thoracic diseases in chest images using advanced deep-learning approaches. The research aims to establish a powerful and effective technique for promptly recognizing multiple pathologies in chest radiographs, which holds significant implications for patient outcomes and healthcare resources. Additionally, the study investigates the potential benefits of data augmentation, transfer learning strategies, and multimodal data integration to enhance the proposed approach's performance and adaptability.