Multimodal Medicine in Glaucoma, Diabetic Retinopathy, and Age-related Macular Degeneration: Application and Prospect

Glaucoma, diabetic retinopathy (DR), and age-related macular degeneration (AMD) are the leading causes of blindness worldwide, and single-modal techniques are insufficient to meet the demands of diagnosis and treatment. Therefore, this article reviews the research on multimodal medical technology in glaucoma, diabetic retinopathy, and age-related macular degeneration. In the diagnosis and treatment of early glaucoma, multimodal fusion can effectively improve the accuracy of diagnosis and grading, and further optimize related decisions. In the diagnosis and treatment of DR, the fusion architecture can improve accuracy, but the MMDA framework has scarce data. However, the DeepDR-LLM system can improve the efficiency of primary care. In the diagnosis and treatment of AMD, a dual-stream Convolutional Neural Network (CNN) can optimize classification effects, and anti-VEGF drugs have good therapeutic effects. DR has a protective effect on AMD. However, current technologies still have problems such as insufficient fusion. In the future, it is necessary to further optimize technical data, break through transformation, and promote the application of multimodal technology in ophthalmology.