Artificial intelligence applied to diabetes complications: a bibliometric analysis

Abstract

Background and aims: Artificial intelligence (AI)-driven medical assistive technology has been widely used in the diagnosis, treatment and prognosis of diabetes complications. Here we conduct a bibliometric analysis of scientific articles in the field of AI in diabetes complications to explore current research trends and cutting-edge hotspots. Methodology: On April 20, 2024, we collected and screened relevant articles published from 1988 to 2024 from PubMed. Based on bibliometric tools such as CiteSpace, Vosviewer and bibliometix, we construct knowledge maps to visualize literature information, including annual scientific production, authors, countries, institutions, journals, keywords and research hotspots. Results: A total of 935 articles meeting the criteria were collected and analyzed. The number of annual publications showed an upward trend. Raman, Rajiv published the most articles, and Webster, Dale R had the highest collaboration frequency. The United States, China, and India were the most productive countries. Scientific Reports was the journal with the most publications. The three most frequent diabetes complications were diabetic retinopathy, diabetic nephropathy, and diabetic foot. Machine learning, diabetic retinopathy, screening, deep learning, and diabetic foot are still being researched in 2024. Conclusion: Global AI research on diabetes complications is expected to increase further. The investigation of AI in diabetic retinopathy and diabetic foot will be the focus of research in the future.