Abstract: In recent years, artificial intelligence (AI) technology has gradually penetrated into many medical specialties, bringing unprecedented changes to the medical field. At present, with the application of AI technology in the field of ophthalmology developing rapidly, AI diagnosis is rapid, highly accurate and objective, which can optimise the diagnosis and treatment mode of ophthalmology patients and greatly improve the efficiency of clinical diagnosis. Some AI ophthalmic imaging research has been translated into products, and therefore both domestic and international AI retinal imaging products are now available. However, due to various factors such as training data, R&D capability, clinical validation and market adaptation, many research outcomes still wait to to be translated. Therefore, we propose new therapeutic regimens of retinal diseases and analyze the underlying constraints to technology translation in AI research, with the hope of improving the use of AI technology in the diagnosis and treatment of fundus diseases.