Bibliometric Analysis of Deep Learning Applications in Diabetes

This study provides a bibliometric review of deep learning applications in diabetes between 2018 and 2022, with an analysis the 2201 publications. highlights influential aspects research from perspective. Deep has drawn significant interest researchers, particularly those working diabetes. Two well-known databases: Web Science Scopus, each which having its own data format, are combined into single format using R programming language Studio, duplicates removed. The Bibliometrix package is used to conduct quantitative analysis, includes highlighting primary journals, works that have been referenced most, authors, nations, institutions produced as well keyword clustering, paper split sub-periods track theme progression, top trend analysis. findings demonstrate notable increase publications since 2018. A plethora studies conducted on practical treat diabetes, dramatically rising. IEEE Access, Scientific Reports, Computers Biology Medicine three most relevant journals. China productive highly cited, while USA comes second. Accuracy, atrial fibrillation, heart infarction recently hot topics. frequently words human, article, mellitus. help academics better understand area this related field, one hottest fields Artificial Intelligence.