Visual analysis of research trends in diabetes-associated dry eye via bibliometrics

Age, gender, diabetes duration, and diabetic retinopathy are strongly associated with the development of DADE, but the impact of other systemic factors require further investigation. With high prevalence of dry eye in Asia, valuable resources like the Korea National Health and Nutrition Examination Survey (KNHANES) database offer crucial data for developing risk prediction models for DADE. Building risk prediction models using machine learning algorithms is a promising future research direction, enabling physicians to identify high-risk individuals and implement early interventions.