Application status and progress of artificial intelligence in dry eye associated with meibomian gland dysfunction

In recent years, the incidence of dry eye disease has been increasing year by year due to environmental changes and some people’s overuse of eyes.As the main type of dry eye disease, hyperevaporative dry eye disease is mostly caused by meibomian gland dysfunction (MGD) resulted from abnormal quality or quantity of lipid layer.Due to differences in diagnosis and classification, there is no unified standard for the treatment of this disease at present.The clinician’s judgment of the diagnosis and treatment effect and follow-up management are limited.With the availability of big data, improvements in computer graphics processing and mathematical models, artificial intelligence (AI) is widely used in the medical field.AI systems can utilize technologies such as machine learning and deep learning to exert advanced problem-solving capabilities, making diagnosis more objective and improving diagnosis and treatment efficiency.The application of AI in ophthalmology is mainly based on the auxiliary diagnosis of eye images and the screening of eye diseases, which reduces the dependence of the medical system on manual labor, makes the screening and diagnosis of eye diseases faster, more convenient and more consistent, alleviates the medical burden, and thus significantly improves the efficiency and cost-effectiveness of medical services.At present, the application of AI in cataract, glaucoma, diabetic retinopathy and other fields is becoming more and more mature, and the research in the field of MGD-related dry eye has also made certain progress.This article reviewed the application status and progress of AI in MGD-related dry eye.

Artificial intelligence; Deep learning; Machine learning; Dry eye; Meibomian gland dysfunction; Image classification and analysis