Eye Disease Screening

Eye disease screening research focuses on developing accurate and reliable diagnostic tools, particularly for populations with limited access to specialists. Current efforts center on advanced machine learning models, including multi-modal approaches that integrate information from various imaging sources and incorporate uncertainty quantification techniques like those based on Student's t-distributions, to improve diagnostic confidence and robustness. These advancements aim to enhance diagnostic accuracy, address biases in existing algorithms, and ultimately improve the efficiency and equity of eye disease detection and management globally.