[The innovation and challenge of artificial intelligence in the whole process management of fundus disease]

Artificial intelligence (AI) has demonstrated revolutionary potential and wide-ranging applications in the comprehensive management of fundus diseases, yet it faces challenges in clinical translation, data quality, algorithm interpretability, and cross-cultural adaptability. AI has proven effective in the efficient screening, accurate diagnosis, personalized treatment recommendations, and prognosis prediction for conditions such as diabetic retinopathy, age-related macular degeneration, and other fundus diseases. However, there is a significant gap between the need for large-scale, high-quality, and diverse datasets and the limitations of current research data. Additionally, the black-box nature of AI algorithms, the acceptance by clinicians and patients, and the generalizability of these algorithms pose barriers to their widespread clinical adoption. Researchers are addressing these challenges through approaches such as federated learning, standardized data collection, and prospective trials to enhance the robustness, interpretability, and practicality of AI systems. Despite these obstacles, the benefits of AI in fundus disease management are substantial. These include improved screening efficiency, support for personalized treatment, the discovery of novel disease characteristics, and the development of precise treatment strategies. Moreover, AI facilitates the advancement of telemedicine through 5G and the Internet of Things. Future research should continue to tackle existing issues, fully leverage the potential of AI in the prevention and treatment of fundus diseases, and advance intelligent, precise, and remote ophthalmic services to meet global eye health needs.