Overview of global publications on machine learning in diabetic retinopathy from 2011 to 2021: Bibliometric analysis.

To comprehensively analyze and discuss the publications on machine learning (ML) in diabetic retinopathy (DR) following a bibliometric approach. The global publications on ML in DR from 2011 to 2021 were retrieved from the Web of Science Core Collection (WoSCC) database. We analyzed the publication and citation trend over time and identified highly-cited articles, prolific countries, institutions, journals and the most relevant research domains. VOSviewer and Wordcloud are used to visualize the mainstream research topics and evolution of subtopics in the form of co-occurrence maps of keywords. By analyzing a total of 1147 relevant publications, this study found a rapid increase in the number of annual publications, with an average growth rate of 42.68%. India and China were the most productive countries. IEEE Access was the most productive journal in this field. In addition, some notable common points were found in the highly-cited articles. The keywords analysis showed that "diabetic retinopathy", "classification", and "fundus images" were the most frequent keywords for the entire period, as automatic diagnosis of DR was always the mainstream topic in the relevant field. The evolution of keywords highlighted some breakthroughs, including "deep learning" and "optical coherence tomography", indicating the advance in technologies and changes in the research attention. As new research topics have emerged and evolved, studies are becoming increasingly diverse and extensive. Multiple modalities of medical data, new ML techniques and constantly optimized algorithms are the future trends in this multidisciplinary field.

Shao A ，Jin K ，Li Y ，Lou L ，Zhou W ，Ye J ... -  《Frontiers in Endocrinology》

Global trends and performances in diabetic retinopathy studies: A bibliometric analysis.

The objective of this study is to conduct a comprehensive bibliometric analysis to identify and evaluate global trends in diabetic retinopathy (DR) research and visualize the focus and frontiers of this field. Diabetic retinopathy-related publications from the establishment of the Web of Science (WOS) through 1 November 2022 were retrieved for qualitative and quantitative analyses. This study analyzed annual publication counts, prolific countries, institutions, journals, and the top 10 most cited literature. The findings were presented through descriptive statistics. VOSviewer 1.6.17 was used to exhibit keywords with high frequency and national cooperation networks, while CiteSpace 5.5.R2 displayed the timeline and burst keywords for each term. A total of 10,709 references were analyzed, and the number of publications continuously increased over the investigated period. America had the highest h-index and citation frequency, contributing to the most influence. China was the most prolific country, producing 3,168 articles. The University of London had the highest productivity. The top three productive journals were from America, and Investigative Ophthalmology Visual Science had the highest number of publications. The article from Gulshan et al. (2016; co-citation counts, 2,897) served as the representative and symbolic reference. The main research topics in this area were incidence, pathogenesis, treatment, and artificial intelligence (AI). Deep learning, models, biomarkers, and optical coherence tomography angiography (OCTA) of DR were frontier hotspots. Bibliometric analysis in this study provided valuable insights into global trends in DR research frontiers. Four key study directions and three research frontiers were extracted from the extensive DR-related literature. As the incidence of DR continues to increase, DR prevention and treatment have become a pressing public health concern and a significant area of research interest. In addition, the development of AI technologies and telemedicine has emerged as promising research frontiers for balancing the number of doctors and patients.

Xiao H ，Tang J ，Zhang F ，Liu L ，Zhou J ，Chen M ，Li M ，Wu X ，Nie Y ，Duan J ... -  《Frontiers in Public Health》

Artificial intelligence in diabetic retinopathy: Bibliometric analysis.

The use of artificial intelligence in diabetic retinopathy has become a popular research focus in the past decade. However, no scientometric report has provided a systematic overview of this scientific area. We utilized a bibliometric approach to identify and analyse the academic literature on artificial intelligence in diabetic retinopathy and explore emerging research trends, key authors, co-authorship networks, institutions, countries, and journals. We further captured the diabetic retinopathy conditions and technology commonly used within this area. Web of Science was used to collect relevant articles on artificial intelligence use in diabetic retinopathy published between January 1, 2012, and December 31, 2022 . All the retrieved titles were screened for eligibility, with one criterion that they must be in English. All the bibliographic information was extracted and used to perform a descriptive analysis. Bibliometrix (R tool) and VOSviewer (Leiden University) were used to construct and visualize the annual numbers of publications, journals, authors, countries, institutions, collaboration networks, keywords, and references. In total, 931 articles that met the criteria were collected. The number of annual publications showed an increasing trend over the last ten years. Investigative Ophthalmology & Visual Science (58/931), IEEE Access (54/931), and Computers in Biology and Medicine (23/931) were the most journals with most publications. China (211/931), India (143/931, USA (133/931), and South Korea (44/931) were the most productive countries of origin. The National University of Singapore (40/931), Singapore Eye Research Institute (35/931), and Johns Hopkins University (34/931) were the most productive institutions. Ting D. (34/931), Wong T. (28/931), and Tan G. (17/931) were the most productive researchers. This study summarizes the recent advances in artificial intelligence technology on diabetic retinopathy research and sheds light on the emerging trends, sources, leading institutions, and hot topics through bibliometric analysis and network visualization. Although this field has already shown great potential in health care, our findings will provide valuable clues relevant to future research directions and clinical practice.

Poly TN ，Islam MM ，Walther BA ，Lin MC ，Jack Li YC ... -  《-》

Bibliometric and visualized analysis of ocular drug delivery from 2001 to 2020.

To perform a bibliometric analysis in the field of ocular drug delivery research to characterize the current international trends and to present visual representations of the past and emerging trends on ocular drug delivery research over the past decade. In this cross-sectional study, a bibliometric analysis of data retrieved and extracted from the Web of Science Core Collection (WoSCC) database was performed to analyze evolution and theme trends on ocular drug delivery research from January 1, 2001, to December 31, 2020. A total of 4334 articles on ocular drug delivery were evaluated for specific characteristics, such as publication year, journals, authors, institutions, countries/regions, references, and keywords. Co-authorship analysis, co-occurrence analysis, co-citation analysis, and network visualization were constructed by VOSviewer. Some important subtopics identified by bibliometric characterization were further discussed and reviewed. From 2001 to 2020, the annual global publications increased by 746.15%, from 52 to 440. International Journal of Pharmaceutics published the most manuscripts (250 publications) and produced the highest citations (9509 citations), followed by Investigative Ophthalmology & Visual Science (202 publications) and Journal of Ocular Pharmacology and Therapeutics (136 publications). The United States (1289 publications, 31,512 citations), the University of Florida (82 publications, 2986 citations), and Chauhan, Anuj (52 publications, 2354 citations) were the most productive and impactful institution, country, and author respectively. The co-occurrence cluster analysis of the top 100 keywords form five clusters: (1) micro/nano ocular drug delivery systems; (2) the treatment of inflammation and posterior diseases; (3) macroscopic ocular drug delivery systems/devices; (4) the characteristics of drug delivery systems; (5) and the ocular drug delivery for glaucoma treatment. Diabetic macular edema, anti-VEGF, ranibizumab, bevacizumab, micelles and latanoprost, were the latest high-frequency keywords, indicating the emerging frontiers of ocular drug delivery. Further discussions into the subtopics were provided to assist researchers to determine the range of research topics and plan research direction. Over the last two decades there has been a progressive increase in the number of publications and citations on research related to ocular drug delivery across many countries, institutions, and authors. The present study sheds light on current trends, global collaboration patterns, basic knowledge, research hotspots, and emerging frontiers of ocular drug delivery. Novel solutions for ocular drug delivery and the treatment of inflammation and posterior diseases were the major themes over the last 20 years.

Peng C ，Kuang L ，Zhao J ，Ross AE ，Wang Z ，Ciolino JB ... -  《-》

Global research of artificial intelligence in strabismus: a bibliometric analysis.

To analyze the global publications on artificial intelligence (AI) in strabismus using a bibliometric approach. The Web of Science Core Collection (WoSCC) database was used to retrieve all of the publications on AI in strabismus from 2002 to 2023. We analyzed the publication and citation trend and identified highly-cited articles, prolific countries, institutions, authors and journals, relevant research domains and keywords. VOSviewer (software) and Bibliometrix (package) were used for data analysis and visualization. By analyzing a total of 146 relevant publications, this study found an overall increasing trend in the number of annual publications and citations in the last decade. USA was the most productive country with the closest international cooperation. The top 3 research domains were Ophthalmology, Engineering Biomedical and Optics. Journal of AAPOS was the most productive journal in this field. The keywords analysis showed that "deep learning" and "machine learning" may be the hotspots in the future. In recent years, research on the application of AI in strabismus has made remarkable progress. The future trends will be toward optimized technology and algorithms. Our findings help researchers better understand the development of this field and provide valuable clues for future research directions.

Zhou Z ，Zhang X ，Tang X ，Grzybowski A ，Ye J ，Lou L ... -  《Frontiers in Medicine》