Automated Medical Report Generation using Deep Learning

This paper surveys recent advancements in deep learning for automated medical report generation, inspired by image captioning techniques. It explores key methodologies, including CNN-based feature extraction, RNNs, attention mechanisms, and reinforcement learning. The study discusses datasets, evaluation metrics, and real-world applications, emphasizing benefits like improved efficiency and reduced human error. Challenges such as data imbalance and model interpretability are addressed, along with future research directions aimed at enhancing diagnostic accuracy and clinical workflows.