Age Related Macular Degeneration

Age-related macular degeneration (AMD) is a leading cause of vision loss, and research focuses on improving early detection and predicting disease progression to enable timely intervention. Current studies leverage deep learning, employing convolutional neural networks (CNNs), recurrent neural networks (RNNs like LSTMs), and transformer architectures, often incorporating multi-modal data (fundus photography and optical coherence tomography) and longitudinal imaging to enhance diagnostic accuracy and prognostic capabilities. These advancements aim to improve AMD diagnosis and management, potentially leading to more effective treatment strategies and improved patient outcomes.