人工智能应用于糖尿病视网膜病变的可视化分析 后印本

Краткое изложение: Background In recent years, artificial intelligence (AI) has shown rapid development in the medical field, and its application in diabetic retinopathy (DR) has been expanding. Objective To summarize the application of AI in DR through bibliometric analysis and elucidate the current status, hot spots and emerging trends of AI-related research in DR, with a view to providing ideas for future research. Methods Using the Web of Science database as the source, we searched the literature related to AI applications in DR from the database build to 2022-11-04 and used CiteSpace software to visualize and analyze the number of articles, countries, institutions, authors, co-citation and keywords in the literature. Results A total of 1770 papers were obtained, with an overall increasing trend in the number of publications and a peak of 402 papers in 2021. China was the top country in terms of the number of publications (440), and the UK was the country with the highest intermediary centrality (0.26). A total of 436 institutions were included in the institutional collaboration network mapping, represented by Sun Yat-sen University and Capital Medical University. A total of 601 authors were included in the author collaboration network mapping, represented by JIA Y and THOMAS H. Three highly cited authors, GULSHAN V, ABRAMOFF M and TING D, have made important contributions to the field. OPHTHALMOLOGY, INVEST OPHTH VIS SCI and IEEE T MED IMAGING are the three most influential journals in the field of AI applied to DR. The research hot spots were mainly focused on lesion segmentation and DR diagnosis. The future research trends may be efficacy prediction of diabetic macular edema as a complication of DR, disease management and improvement of AI algorithm performance. Conclusion Researchers can refer to the research hot spots and trends shown by this visual analysis, focusing on AI in DR diagnosis, disease management and improvement of AI algorithm performance.